Patent Publication Number: US-2019199748-A1

Title: Deception system

Description:
CROSS REFERENCES TO RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 15/467,647, filed on Mar. 23, 2017, which is a continuation of U.S. patent application Ser. No. 15/467,276 filed on Mar. 23, 2017, issued as U.S. Pat. No. 10,218,741 on Feb. 26, 2019, and which claims the benefit of and priority to Indian Provisional Application Number 201741001265, filed on Jan. 12, 2017. Each of the preceding is incorporated herein by reference in their entirety. 
    
    
     BRIEF SUMMARY 
     Cyber-vaccination and cyber antibodies borrow concepts known in medicine. In medicine, a vaccine often uses a weakened or killed organism to stimulate the human body to create antibodies against the organism. Similarly, in the realm of computing, the tools used by malware programs can be used against the very same malware programs to defend computing systems from being infected by these malware programs. 
     Provided are systems, methods, including computer-implemented methods, and computer-program products for a cyber-vaccination technique. In various implementations, the cyber-vaccination technique includes using a network device that is infected by a malware program to determining a marker generated by the malware program. The marker may indicate to the malware program that the network device has been infected by the malware program. Determining the marker can include identifying a placement of the marker on the network device. The technique further includes identifying one or more other network devices that have not previously been infected by the malware program. The technique further includes automatically distributing copies of the marker. When a copy of the marker is received at one of the previously identified, uninfected network devices, the identified network device can place the marker on the identified network device according to the identified placement. 
     In various implementations, determining the marker according to the cyber-vaccination technique includes comparing a first snapshot of the infected network device with a second snapshot of the infected network device. The first snapshot was taken before the infection by the malware program occurred, and the second snapshot was taken after the infection occurred. Determining the marker further includes determining one or more differences between the first snapshot and the second snapshot, and identifying a difference from the among the differences as the marker. 
     In some implementations, determining the marker includes determining a change in a system registry of the network device. In some implementations, determining the marker includes determining a change in a file system of the network device. In some implementations, determining the marker includes identifying a process running on the network device. In some implementations, determining the marker includes identifying a user logged in to the network device. In some implementations, determining the marker includes determining a change in a system memory of the network device. In some implementations, determining the marker includes identifying an open port of the network device. 
     In various implementations, the cyber-vaccination technique further includes identifying the network device as infected by the malware program. In various implementations, the technique further includes activating the malware program on the network device. 
     In various implementations, presence of a copy of the marker on an uninfected network device from the one or more other network devices represents the network device as infected by the malware program. 
     In various implementations, determining the marker occurs in real time. 
     In various implementations, automatically distributing the copies of the marker includes using a remote administration tool. 
     Also provided are systems, methods, and computer-program products for a cyber-antibody technique. In various implementations, the cyber-antibody technique includes using a network device that has been infected with an unknown malware program to monitor packets sent by this network device onto a network. The technique further includes identifying a packet that is associated with the unknown malware program. The packet can be identified from among the monitored packets, and identifying the packet can include determining a characteristic of the packet. The technique further includes identifying other packets having a characteristic similar to the characteristic of the identified packet. The technique further includes inserting data associated with a known malware program into the one or more other packets. The technique further includes automatically distributing the characteristic of the packet. When the characteristic is received at another network device, the characteristic can be used to identify additional packets having a characteristic similar to the characteristic of the packet. 
     In various implementations, in accordance with the cyber antibody technique, identifying the packet associated with the malware program includes determining a process that generated the packet. 
     In various implementations, determining the characteristic of the packet includes examining a header portion of the packet. In some implementations, examining the header portion includes identifying one or more of a source address, a destination address. a network service type, an identifier, a class, or a label. 
     In various implementations, determining the characteristic of the packet includes examining a payload portion of the packet. In some implementations, examining the payload portion includes identifying for a character string. 
     In various implementations, the data associated with the known malware program infects the one or more other packets with the known malware program. In some implementations, the known malware program is blocked by network security infrastructure devices. 
     In various implementations, monitoring the packets includes monitoring for minutes, hours, days, or weeks. 
     In various implementations, the cyber-antibody technique further includes receiving a new characteristic from the network. The new characteristic may be associated with a new malware program. The technique further includes configuring a process with the new characteristic. The process can insert the digital signature in other packets with a similar characteristic. 
     In various implementations, identifying the packet occurs in real time. 
     In various implementations, automatically distributing the characteristic includes using remote administration tools. 
     Also provided are systems, methods, and computer-program products for a generic cyber-vaccination technique. In various implementations, the generic cyber-vaccination technique includes using a network device to determine one or more characteristics of a testing environment. The testing environment can used to analyze malware programs. The technique further includes configuring a production network device used in network operations, which exclude analyzing malware programs. The production network device can configured using the characteristics of the testing environment. Configuring the production network device with the characteristics can cause the production network device to resemble the testing environment. 
     In various implementations, the testing environment involved in the generic cyber-vaccination technique includes a virtual machine. In various implementations, the one or more characteristics of the testing environment include a process associated with a virtual machine. In various implementations, the characteristics include a particular Media Access Control (MAC) address. In various implementations, characteristics include an entry in a system registry. In various implementations, the characteristics include one or more of a structure or content of a file system. In various implementations, the characteristics include an execution path of a process associated with the testing environment. 
     In various implementations, the generic cyber-vaccination technique includes automatically distributing the characteristics of the testing environment to one or more other network devices. 
     In various implementations, the generic cyber-vaccination technique includes configuring the network device with the one or more characteristics. 
     In various implementations, the generic cyber-vaccination technique includes receiving a malware program. The malware program may be configured to execute upon determining that the malware program is not in the testing environment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Illustrative embodiments are described in detail below with reference to the following figures: 
         FIG. 1  illustrates an example of a network threat detection and analysis system, in which various implementations of a deception-based security system can be used; 
         FIGS. 2A-2D  provide examples of different installation configurations that can be used for different customer networks; 
         FIG. 3A-3B  illustrate examples of customer networks where some of the customer networks&#39; network infrastructure is “in the cloud,” that is, is provided by a cloud services provider; 
         FIG. 4  illustrates an example of an enterprise network; 
         FIG. 5  illustrates a general example of an Internet-of-Things network; 
         FIG. 6  illustrates an example of an Internet-of-Things network, here implemented in a private home; 
         FIG. 7  illustrates an Internet-of-Things network, here implemented in a small business; 
         FIG. 8  illustrates an example of the basic operation of an industrial control system; 
         FIG. 9  illustrates an example of a SCADA system, here used for distributed monitoring and control; 
         FIG. 10  illustrates an example of a distributed control; 
         FIG. 11  illustrates an example of a PLC implemented in a manufacturing control process; 
         FIGS. 12A-12C  illustrate an example of a network, in which cyber vaccination techniques can be implemented; 
         FIG. 13  illustrates another example of a network in which cyber vaccination techniques can be implemented; 
         FIGS. 14A-14C  illustrate an example of a network, in which cyber antibody techniques can be implemented; 
         FIG. 15  illustrates another example of a network in which cyber antibody techniques can be implemented; 
         FIG. 16  illustrates an example of a network that includes a sandbox testing environment; and 
         FIG. 17  illustrates an example of a generic cyber vaccination technique. 
     
    
    
     DETAILED DESCRIPTION 
     Network deception mechanisms, often referred to as “honeypots,” “honey tokens,” and “honey nets,” among others, defend a network from threats by distracting or diverting the threat. Honeypot-type deception mechanisms can be installed in a network for a particular site, such as a business office, to act as decoys in the site&#39;s network. Honeypot-type deception mechanisms are typically configured to be indistinguishable from active, production systems in the network. Additionally, such deception mechanisms are typically configured to be attractive to a network threat by having seemingly valuable data and/or by appearing vulnerable to infiltration. Though these deception mechanisms can be indistinguishable from legitimate parts of the site network, deception mechanisms are not part of the normal operation of the network, and would not be accessed during normal, legitimate use of the site network. Because normal users of the site network would not normally use or access a deception mechanism, any use or access to the deception mechanism is suspected to be a threat to the network. 
     “Normal” operation of a network generally includes network activity that conforms with the intended purpose of a network. For example, normal or legitimate network activity can include the operation of a business, medical facility, government office, education institution, or the ordinary network activity of a private home. Normal network activity can also include the non-business-related, casual activity of users of a network, such as accessing personal email and visiting websites on personal time, or using network resources for personal use. Normal activity can also include the operations of network security devices, such as firewalls, anti-virus tools, intrusion detection systems, intrusion protection systems, email filters, adware blockers, and so on. Normal operations, however, exclude deceptions mechanisms, in that deception mechanisms are not intended to take part in business operations or casual use. As such, network users and network systems do not normally access deceptions mechanisms except perhaps for the most routine network administrative tasks. Access to a deception mechanism, other than entirely routine network administration, may thus indicate a threat to the network. 
     Threats to a network can include active attacks, where an attacker interacts or engages with systems in the network to steal information or do harm to the network. An attacker may be a person, or may be an automated system. Examples of active attacks include denial of service (DoS) attacks, distributed denial of service (DDoS) attacks, spoofing attacks, “man-in-the-middle” attacks, attacks involving malformed network requests (e.g. Address Resolution Protocol (ARP) poisoning, “ping of death,” etc.), buffer, heap, or stack overflow attacks, and format string attacks, among others. Threats to a network can also include self-driven, self-replicating, and/or self-triggering malicious software. Malicious software can appear innocuous until activated, upon which the malicious software may attempt to steal information from a network and/or do harm to the network. Malicious software is typically designed to spread itself to other systems in a network. Examples of malicious software include ransomware, viruses, worms, Trojan horses, spyware, keyloggers, rootkits, and rogue security software, among others. 
     Anti-virus tools and so-called “sandbox” techniques can be used to detect and block malware, including for example ransomware, adware, bots, rootkits, spyware, Trojan horses, viruses, worms, and other types of malicious programs. Anti-virus tools include those produced by McAfee®, Kaspersky®, and Symantec®, among others. Sandbox techniques for detecting and blocking malware typically use a tightly controlled and closely monitored environment, referred to as a sandbox or testing environment, in which untrusted programs can be run and watched. Because the testing environment is carefully controlled and isolated, any harm done by the untrusted program will not spread to other computing systems. Sandbox testing environments are frequently virtual environments, which can be quickly reset to a clean state when testing is complete. Sandbox environments include those produced by FireEye®, among others. 
     Sandbox techniques and similar techniques are frequently used to analyze newly discovered malware. A malware program can be released into the sandbox, where the malware program can be studied and/or reverse engineered by security experts. Reverse engineering the malware can include determining the manner in which the malware operates, the harm intended by the malware, the manner in which the malware replicates itself, and/or identifying the point of entry of the malware into a network or computing system. Security engineers can generate a digital signature for the malware, for example by executing a program or function on data associated with the malware (e.g., a file, a file name, a process, a network packets, etc.). For example, the digital signature can be generated by executing a hash function on an executable file from which the malware program was launched. As used herein, the digital signature is typically a unique identifier for a specific malware program and can be used to identify the malware when, for example, anti-virus tools scan computer data. 
     Reverse engineering and producing digital signatures for each new malware program and each new variant of a malware program may not be possible or practicable. For example, 350,000 ransomware variants were released in just 2015. Furthermore, while digital signatures can be used to contain malware outbreaks, malware designers have been able to thwart identification through digital signatures. For example, some malware have been written as oligomorphic, polymorphic, or metamorphic programs, which can encrypt parts of themselves, or otherwise modify themselves. These techniques can disguise the malware, so that the malware will not match a digital signature in a block list. 
     Digital signatures also cannot defend against a “zero day” virus or malware. A zero day virus or malware is a previously unknown malicious program, for which a digital signature is not yet available. Anti-virus tools and other network security infrastructure may not be able to identify and block zero-day malware. 
     Security experts have developed other approaches for identifying malware that do not rely exclusively on digital signatures. For example, some network security products use behavioral detection techniques, heuristic detection techniques, artificial intelligence, machine learning, containerization, and sandbox testing environments, among other things. Challenges faced by these approaches include filtering out of false positives, convenience of configuration for ordinary users (e.g., non-security experts), and false negatives, that is, failing to detect or identify a malware program. 
     Once malware has been detected, a typical incident response is to manually isolate the compromised computing system. For example, the computing system can be shut down or the computing system&#39;s network access can be disabled. By isolating the compromised computing system, network administrators can attempt to prevent or limit the spread of the malware to other devices in the network. Such manual intervention, however, relies on the vigilance, speed, and skill of human operators, who may not be able to keep up with the sheer volume of malware attacks. Isolation of compromised computing systems can be accomplished in an automated fashion, but automated isolation relies on the ability of tools that can detect that the system has been compromised. Such tools may have varying degrees of capability. 
     In various implementations, provided are techniques for “vaccinating” a computing system against a malware attack, without needing to reverse engineer the malware program, or otherwise expend much effort analyzing the malware program. In various implementations, a cyber-vaccine technique includes determining a marker generated by the malware program. Malware programs often avoid re-infecting a system twice, and so use various markers, such as files, processes, registry entries, and other data to identify systems the malware program has already infected. 
     Cyber-vaccination techniques can be used to identify such markers. Once identified, the markers can be distributed to other computing systems, including ones not yet infected by the malware. Should the malware spread to these computing systems, the malware may detect the marker, and not infect these computing systems. Computing systems can thus be protected from infection. 
     In various implementations, also provided are techniques for providing computing systems with “antibodies” against malware attacks that use seemingly innocuous network communications to receive instructions from a malicious entity and/or to steal data. In some cases, malware programs establish “command and control” communication channels with entities outside of a local area network, such as somewhere on the Internet. Using a command and control channel the malware can receive instructions and/or send valuable data to the outside entity. The network communications with the outside entity can appear safe and innocent. For example, the communications can be social media posts, forum posts, and/or other network communications that, alone, may do no harm. 
     Cyber-antibody techniques can be used to identify such network traffic. Once identified, this seemingly harmless network traffic can be deliberately “tainted” or made to carry a known malware signature. The network traffic thus appears to contain malware, and because known malware is used, a network&#39;s security infrastructure will block the network traffic from reaching the Internet. The malware&#39;s command and control channel can thus be cut off, possibly preventing the malware from doing harm. The cyber-antibody can further be distributed to the computing systems in a network, so that, should these systems become infected with the same malware, the malware will be unable to establish a command and control communication channel. These computing systems can thus be protected from this particular malware. 
     In various implementations, also provided are techniques for providing a generic cyber-vaccine for computing systems in a network. As noted above, malware programs are sometimes designed to detect when the malware program is in a sandbox testing environment. For example, a malware program may look for the presence of particular processes or files. A generic cyber-vaccine can replicate the characteristics of a testing environment on production systems, such that productions systems—which would not be used for analyzing malware—resemble a testing environment. Malware programs designed not to trigger in a testing environment may thus not trigger on computing systems that have the generic cyber-vaccine. In this way, these computing systems can be protected from infection that are capable of detecting their environment. 
     Further techniques that are related to the techniques and systems described herein can be found in the following related applications, each of which are hereby incorporated by reference in their entireties: U.S. application Ser. No. 15,454,181, filed on Mar. 9, 2017, titled “ACTIVE DECEPTION SYSTEM;” U.S. application Ser. No. 15/785,083, filed on Oct. 16, 2017, titled “SYSTEMS AND METHODS FOR IDENTIFYING A COMMON ATTACK TECHNIQUE USING DECEPTION CONTEXT MINING;” and U.S. application Ser. No. 15/496,724, filed on Apr. 25, 2017, titled “RESPONSIVE DECEPTION MECHANISMS.” 
     I. Deception-Based Security Systems 
       FIG. 1  illustrates an example of a network threat detection and analysis system  100 , in which various implementations of a deception-based security system can be used. The network threat detection and analysis system  100 , or, more briefly, network security system  100 , provides security for a site network  104  using deceptive security mechanisms, a variety of which may be called “honeypots.” The deceptive security mechanisms may be controlled by and inserted into the site network  104  using a deception center  108  and sensors  110 , which may also be referred to as deception sensors, installed in the site network  104 . In some implementations, the deception center  108  and the sensors  110  interact with a security services provider  106  located outside of the site network  104 . The deception center  108  may also obtain or exchange data with sources located on the Internet  150 . 
     Security mechanisms designed to deceive, sometimes referred to as “honeypots,” may also be used as traps to divert and/or deflect unauthorized use of a network away from the real network assets. A deception-based security mechanism may be a computer attached to the network, a process running on one or more network systems, and/or some other device connected to the network. A security mechanism may be configured to offer services, real or emulated, to serve as bait for an attack on the network. Deception-based security mechanisms that take the form of data, which may be called “honey tokens,” may be mixed in with real data in devices in the network. Alternatively or additionally, emulated data may also be provided by emulated systems or services. 
     Deceptive security mechanisms can also be used to detect an attack on the network. Deceptive security mechanisms are generally configured to appear as if they are legitimate parts of a network. These security mechanisms, however, are not, in fact, part of the normal operation of the network. Consequently, normal activity on the network is not likely to access the security mechanisms. Thus any access over the network to the security mechanism is automatically suspect. 
     The network security system  100  may deploy deceptive security mechanisms in a targeted and dynamic fashion. Using the deception center  108  the system  100  can scan the site network  104  and determine the topology of the site network  104 . The deception center  108  may then determine devices to emulate with security mechanisms, including the type and behavior of the device. The security mechanisms may be selected and configured specifically to attract the attention of network attackers. The security mechanisms may also be selected and deployed based on suspicious activity in the network. Security mechanisms may be deployed, removed, modified, or replaced in response to activity in the network, to divert and isolate network activity related to an apparent attack, and to confirm that the network activity is, in fact, part of a real attack. 
     The site network  104  is a network that may be installed among the buildings of a large business, in the office of a small business, at a school campus, at a hospital, at a government facility, or in a private home. The site network  104  may be described as a local area network (LAN) or a group of LANS. The site network  104  may be one site belonging to an organization that has multiple site networks  104  in one or many geographical locations. In some implementations, the deception center  108  may provide network security to one site network  104 , or to multiple site networks  104  belonging to the same entity. 
     The site network  104  is where the networking devices and users of the an organizations network may be found. The site network  104  may include network infrastructure devices, such as routers, switches hubs, repeaters, wireless base stations, and/or network controllers, among others. The site network  104  may also include computing systems, such as servers, desktop computers, laptop computers, tablet computers, personal digital assistants, and smart phones, among others. The site network  104  may also include other analog and digital electronics that have network interfaces, such as televisions, entertainment systems, thermostats, refrigerators, and so on. 
     The deception center  108  provides network security for the site network  104  (or multiple site networks for the same organization) by deploying security mechanisms into the site network  104 , monitoring the site network  104  through the security mechanisms, detecting and redirecting apparent threats, and analyzing network activity resulting from the apparent threat. To provide security for the site network  104 , in various implementations the deception center  108  may communicate with sensors  110  installed in the site network  104 , using network tunnels  120 . As described further below, the tunnels  120  may allow the deception center  108  to be located in a different sub-network (“subnet”) than the site network  104 , on a different network, or remote from the site network  104 , with intermediate networks (possibly including the Internet  150 ) between the deception center  108  and the site network  104 . 
     In some implementations, the network security system  100  includes a security services provider  106 . In these implementations, the security services provider  106  may act as a central hub for providing security to multiple site networks, possibly including site networks controlled by different organizations. For example, the security services provider  106  may communicate with multiple deception centers  108  that each provide security for a different site network  104  for the same organization. In some implementations, the security services provider  106  is located outside the site network  104 . In some implementations, the security services provider  106  is controlled by a different entity than the entity that controls the site network. For example, the security services provider  106  may be an outside vendor. In some implementations, the security services provider  106  is controlled by the same entity as that controls the site network  104 . 
     In some implementations, when the network security system  100  includes a security services provider  106 , the sensors  110  and the deception center  108  may communicate with the security services provider  106  in order to be connected to each other. For example, the sensors  110 , which may also be referred to as deception sensors, may, upon powering on in the site network  104 , send information over a network connection  112  to the security services provider  106 , identifying themselves and the site network  104  in which they are located. The security services provider  106  may further identify a corresponding deception center  108  for the site network  104 . The security services provider  106  may then provide the network location of the deception center  108  to the sensors  110 , and may provide the deception center  108  with the network location of the sensors  110 . A network location may take the form of, for example, an Internet Protocol (IP) address. With this information, the deception center  108  and the sensors  110  may be able to configure tunnels  120  to communicate with each other. 
     In some implementations, the network security system  100  does not include a security services provider  106 . In these implementations, the sensors  110  and the deception center  108  may be configured to locate each other by, for example, sending packets that each can recognize as coming for the other. Using these packets, the sensors  110  and deception center  108  may be able to learn their respective locations on the network. Alternatively or additionally, a network administrator can configure the sensors  110  with the network location of the deception center  108 , and vice versa. 
     In various implementations, the sensors  110  are a minimal combination of hardware and/or software, sufficient to form a network connection with the site network  104  and a tunnel  120  with the deception center  108 . For example, a sensor  110  may be constructed using a low-power processor, a network interface, and a simple operating system. In various implementations, the sensors  110  provide the deception center  108  with visibility into the site network  104 , such as for example being able to operate as a node in the site network  104 , and/or being able to present or project deceptive security mechanisms into the site network  104 , as described further below. Additionally, in various implementations, the sensors  110  may provide a portal through which a suspected attack on the site network  104  can be redirected to the deception center  108 , as is also described below. 
     In various implementations, the deception center  108  may be configured to profile the site network  104 , deploy deceptive security mechanisms for the site network  104 , detect suspected threats to the site network  104 , analyze the suspected threat, and analyze the site network  104  for exposure and/or vulnerability to the supposed threat. 
     To provide the site network  104 , the deception center  108  may include a deception profiler  130 . In various implementations, the deception profiler may  130  derive information  114  from the site network  104 , and determine, for example, the topology of the site network  104 , the network devices included in the site network  104 , the software and/or hardware configuration of each network device, and/or how the network is used at any given time. Using this information, the deception profiler  130  may determine one or more deceptive security mechanisms to deploy into the site network  104 . 
     In various implementations, the deception profiler may configure an emulated network  116  to emulate one or more computing systems. Using the tunnels  120  and sensors  110 , the emulated computing systems may be projected into the site network  104 , where they serve as deceptions. The emulated computing systems may include address deceptions, low-interaction deceptions, and/or high-interaction deceptions. In some implementations, the emulated computing systems may be configured to resemble a portion of the network. In these implementations, this network portion may then be projected into the site network  104 . 
     In various implementations, a network threat detection engine  140  may monitor activity in the emulated network  116 , and look for attacks on the site network  104 . For example, the network threat detection engine  140  may look for unexpected access to the emulated computing systems in the emulated network  116 . The network threat detection engine  140  may also use information  114  extracted from the site network  104  to adjust the emulated network  116 , in order to make the deceptions more attractive to an attack, and/or in response to network activity that appears to be an attack. Should the network threat detection engine  140  determine that an attack may be taking place, the network threat detection engine  140  may cause network activity related to the attack to be redirected to and contained within the emulated network  116 . 
     In various implementations, the emulated network  116  is a self-contained, isolated, and closely monitored network, in which suspect network activity may be allowed to freely interact with emulated computing systems. In various implementations, questionable emails, files, and/or links may be released into the emulated network  116  to confirm that they are malicious, and/or to see what effect they have. Outside actors can also be allowed to access emulated system, steal data and user credentials, download malware, and conduct any other malicious activity. In this way, the emulated network  116  not only isolated a suspected attack from the site network  104 , but can also be used to capture information about an attack. Any activity caused by suspect network activity may be captured in, for example, a history of sent and received network packets, log files, and memory snapshots. 
     In various implementations, activity captured in the emulated network  116  may be analyzed using a targeted threat analysis engine  160 . The threat analysis engine  160  may examine data collected in the emulated network  116  and reconstruct the course of an attack. For example, the threat analysis engine  160  may correlate various events seen during the course of an apparent attack, including both malicious and innocuous events, and determine how an attacker infiltrated and caused harm in the emulated network  116 . In some cases, the threat analysis engine  160  may use threat intelligence  152  from the Internet  150  to identify and/or analyze an attack contained in the emulated network  116 . The threat analysis engine  160  may also confirm that suspect network activity was not an attack. The threat analysis engine  160  may produce indicators that describe the suspect network activity, including indicating whether the suspect activity was or was not an actual threat. The threat analysis engine  160  may share these indicators with the security community  180 , so that other networks can be defended from the attack. The threat analysis engine  160  may also send the indicators to the security services provider  106 , so that the security services provider  106  can use the indicators to defend other site networks. 
     In various implementations, the threat analysis engine  160  may also send threat indicators, or similar data, to a behavioral analytics engine  170 . The behavioral analytics engine  170  may be configured to use the indicators to probe  118  the site network  104 , and see whether the site network  104  has been exposed to the attack, or is vulnerable to the attack. For example, the behavioral analytics engine  170  may search the site network  104  for computing systems that resemble emulated computing systems in the emulated network  116  that were affected by the attack. In some implementations, the behavioral analytics engine  170  can also repair systems affected by the attack, or identify these systems to a network administrator. In some implementations, the behavioral analytics engine  170  can also reconfigure the site network&#39;s  104  security infrastructure to defend against the attack. 
     The behavioral analytics engine  170  can work in conjunction with a Security Information and Event Management (SIEM)  172  system. In various implementations, SIEM includes software and/or services that can provide real-time analysis of security alerts generates by network hardware and applications. In various implementations, the deception center  108  can communicate with the SIEM  172  system to obtain information about computing and/or networking systems in the site network  104 . 
     Using deceptive security mechanisms, the network security system  100  may thus be able to distract and divert attacks on the site network  104 . The network security system  100  may also be able to allow, using the emulated network  116 , and attack to proceed, so that as much can be learned about the attack as possible. Information about the attack can then be used to find vulnerabilities in the site network  104 . Information about the attack can also be provided to the security community  180 , so that the attack can be thwarted elsewhere. 
     II. Customer Installations 
     The network security system, such as the deception-based system described above, may be flexibly implemented to accommodate different customer networks.  FIGS. 2A-2D  provide examples of different installation configurations  200   a - 200   d  that can be used for different customer networks  202 . A customer network  202  may generally be described as a network or group of networks that is controlled by a common entity, such as a business, a school, or a person. The customer network  202  may include one or more site networks  204 . The customer network&#39;s  202  site networks  204  may be located in one geographic location, may be behind a common firewall, and/or may be multiple subnets within one network. Alternatively or additionally, a customer network&#39;s  202  site networks  204  may be located in different geographic locations, and be connected to each other over various private and public networks, including the Internet  250 . 
     Different customer networks  202  may have different requirements regarding network security. For example, some customer networks  202  may have relatively open connections to outside networks such as the Internet  250 , while other customer networks  202  have very restricted access to outside networks. The network security system described in  FIG. 1  may be configurable to accommodate these variations. 
       FIG. 2A  illustrates one example of an installation configuration  200   a,  where a deception center  208  is located within the customer network  202 . In this example, being located within the customer network  202  means that the deception center  208  is connected to the customer network  202 , and is able to function as a node in the customer network  202 . In this example, the deception center  208  may be located in the same building or within the same campus as the site network  204 . Alternatively or additionally, the deception center  208  may be located within the customer network  202  but at a different geographic location than the site network  204 . The deception center  208  thus may be within the same subnet as the site network  204 , or may be connected to a different subnet within the customer network. 
     In various implementations, the deception center  208  communicates with sensors  210 , which may also be referred to as deception sensors, installed in the site network over network tunnels  220  In this example, the network tunnels  220  may cross one or more intermediate within the customer network  202 . 
     In this example, the deception center  208  is able to communicate with a security services provider  206  that is located outside the customer network  202 , such as on the Internet  250 . The security services provider  206  may provide configuration and other information for the deception center  208 . In some cases, the security services provider  206  may also assist in coordinating the security for the customer network  202  when the customer network  202  includes multiple site networks  204  located in various geographic areas. 
       FIG. 2B  illustrates another example of an installation configuration  200   b,  where the deception center  208  is located outside the customer network  202 . In this example, the deception center  208  may connected to the customer network  202  over the Internet  250 . In some implementations, the deception center  208  may be co-located with a security services provider, and/or may be provided by the security services provider. 
     In this example, the tunnels  220  connect the deception center  208  to the sensors  210  through a gateway  262 . A gateway is a point in a network that connects the network to another network. For example, in this example, the gateway  262  connects the customer network  202  to outside networks, such as the Internet  250 . The gateway  262  may provide a firewall, which may provide some security for the customer network  202 . The tunnels  220  may be able to pass through the firewall using a secure protocol, such as Secure Socket Shell (SSH) and similar protocols. Secure protocols typically require credentials, which may be provided by the operator of the customer network  202 . 
       FIG. 2C  illustrates another example of an installation configuration  200   c,  where the deception center  208  is located inside the customer network  202  but does not have access to outside networks. In some implementations, the customer network  202  may require a high level of network security. In these implementations, the customer network&#39;s  202  connections to the other networks may be very restricted. Thus, in this example, the deception center  208  is located within the customer network  202 , and does not need to communicate with outside networks. The deception center  208  may use the customer networks  202  internal network to coordinate with and establish tunnels  220  to the sensors  210 . Alternatively or additionally, a network administrator may configure the deception center  208  and sensors  210  to enable them to establish the tunnels  220 . 
       FIG. 2D  illustrates another example of an installation configuration  200   d.  In this example, the deception center  208  is located inside the customer network  202 , and further is directly connected to the site network  204 . Directly connected, in this example, can mean that the deception center  208  is connected to a router, hub, switch, repeater, or other network infrastructure device that is part of the site network  204 . Directly connected can alternatively or additionally mean that the deception center  208  is connected to the site network  204  using a Virtual Local Area Network (VLAN). For example, the deception center  208  can be connected to VLAN trunk port. In these examples, the deception center  208  can project deceptions into the site network  204  with or without the use of sensors, such as are illustrated in  FIGS. 2A-2C . 
     In the example of  FIG. 2D , the deception center  208  can also optionally be connected to an outside security services provider  206 . The security services provider  206  can manage the deception center  208 , including providing updated security data, sending firmware upgrades, and/or coordinating different deception centers  208  for different site networks  204  belonging to the same customer network  202 . In some implementations, the deception center  208  can operate without the assistances of an outside security services provider  206 . 
     III. Customer Networks 
     The network security system, such as the deception-based system discussed above, can be used for variety of customer networks. As noted above, customer networks can come in wide variety of configurations. For example, a customer network may have some of its network infrastructure “in the cloud.” A customer network can also include a wide variety of devices, including what may be considered “traditional” network equipment, such as servers and routers, and non-traditional, “Internet-of-Things” devices, such as kitchen appliances. Other examples of customer networks include established industrial networks, or a mix of industrial networks and computer networks. 
       FIG. 3A-3B  illustrate examples of customer networks  302   a - 302   b  where some of the customer networks&#39;  302   a - 302   b  network infrastructure is “in the cloud,” that is, is provided by a cloud services provider  354 . These example customer networks  302   a - 302   b  may be defended by a network security system that includes a deception center  308  and sensors  310 , which may also be referred to as deception sensors, and may also include an off-site security services provider  306 . 
     A cloud services provider is a company that offers some component of cloud computer—such as Infrastructure as a Service (IaaS), Software as a Service (SaaS) or Platform as Service (PaaS)—to other businesses and individuals. A cloud services provider may have a configurable pool of computing resources, including, for example, networks, servers, storage, applications, and services. These computing resources can be available on demand, and can be rapidly provisioned. While a cloud services provider&#39;s resources may be shared between the cloud service provider&#39;s customers, from the perspective of each customer, the individual customer may appear to have a private network within the cloud, including for example having dedicated subnets and IP addresses. 
     In the examples illustrated in  FIGS. 3A-3B , the customer networks&#39;  302   a - 302   b  network is partially in a site network  304 , and partially provided by the cloud services provider  354 . In some cases, the site network  304  is the part of the customer networks  302   a - 302   b  that is located at a physical site owned or controlled by the customer network  302   a - 302   b.  For example, the site network  304  may be a network located in the customer network&#39;s  302   a - 302   b  office or campus. Alternatively or additionally, the site network  304  may include network equipment owned and/or operated by the customer network  302  that may be located anywhere. For example, the customer networks&#39;  302   a - 302   b  operations may consist of a few laptops owned by the customer networks  302   a - 302   b,  which are used from the private homes of the lap tops&#39; users, from a co-working space, from a coffee shop, or from some other mobile location. 
     In various implementations, sensors  310  may be installed in the site network  304 . The sensors  310  can be used by the network security system to project deceptions into the site network  304 , monitor the site network  304  for attacks, and/or to divert suspect attacks into the deception center  308 . 
     In some implementations, the sensors  310  may also be able to project deceptions into the part of the customer networks  302   a - 302   b  network that is provided by the cloud services provider  354 . In most cases, it may not be possible to install sensors  310  inside the network of the cloud services provider  354 , but in some implementations, this may not be necessary. For example, as discussed further below, the deception center  308  can acquire the subnet address of the network provided by the cloud services provider  354 , and use that subnet address the create deceptions. Though these deceptions are projected form the sensors  310  installed in the site network  304 , the deceptions may appear to be within the subnet provided by the cloud services provider  354 . 
     In illustrated examples, the deception center  308  is installed inside the customer networks  302   a - 302   b.  Though not illustrated here, the deception center  308  can also be installed outside the customer networks  302   a - 302   b,  such as for example somewhere on the Internet  350 . In some implementations, the deception center  308  may reside at the same location as the security service provider  306 . When located outside the customer networks  302   a - 302   b,  the deception center  308  may connect to the sensors  310  in the site network  304  over various public and/or private networks. 
       FIG. 3A  illustrates an example of a configuration  300   a  where the customer network&#39;s  302   a  network infrastructure is located in the cloud and the customer network  302   a  also has a substantial site network  304 . In this example, the customer may have an office where the site network  304  is located, and where the customer&#39;s employees access and use the customer network  302   a.  For example, developers, sales and marketing personnel, human resources and finance employees, may access the customer network  302   a  from the site network  304 . In the illustrated example, the customer may obtain applications and services from the cloud services provider  354 . Alternatively or additionally, the cloud services provider  354  may provide data center services for the customer. For example, the cloud services provider  354  may host the customer&#39;s repository of data (e.g., music provided by a streaming music service, or video provided by a streaming video provider). In this example, the customer&#39;s own customers may be provided data directly from the cloud services provider  354 , rather than from the customer network  302   a.    
       FIG. 3B  illustrates and example of a configuration  300   b  where the customer network&#39;s  302   b  network is primarily or sometimes entirely in the cloud. In this example, the customer network&#39;s  302   b  site network  304  may include a few laptops, or one or two desktop servers. These computing devices may be used by the customer&#39;s employees to conduct the customer&#39;s business, while the cloud services provider  354  provides the majority of the network infrastructure needed by the customer. For example, a very small company may have no office space and no dedicated location, and have as computing resources only the laptops used by its employees. This small company may use the cloud services provider  354  to provide its fixed network infrastructure. The small company may access this network infrastructure by connecting a laptop to any available network connection (e.g, in a co-working space, library, or coffee shop). When no laptops are connected to the cloud services provider  354 , the customer network  302  may be existing entirely within the cloud. 
     In the example provided above, the site network  304  can be found wherever the customer&#39;s employees connect to a network and can access the cloud services provider  354 . Similarly, the sensors  310  can be co-located with the employees&#39; laptops. For example, whenever an employee connects to a network, she can enable a sensor  310 , which can then project deceptions into the network around her. Alternatively or additionally, sensors  310  can be installed in a fixed location (such as the home of an employee of the customer) from which they can access the cloud services provider  354  and project deceptions into the network provided by the cloud services provider  354 . 
     The network security system, such as the deception-based system discussed above, can provide network security for a variety of customer networks, which may include a diverse array of devices.  FIG. 4  illustrates an example of an enterprise network  400 , which is one such network that can be defended by a network security system. The example enterprise network  400  illustrates examples of various network devices and network clients that may be included in an enterprise network. The enterprise network  400  may include more or fewer network devices and/or network clients, and/or may include network devices, additional networks including remote sites  452 , and/or systems not illustrated here. Enterprise networks may include networks installed at a large site, such as a corporate office, a university campus, a hospital, a government office, or a similar entity. An enterprise network may include multiple physical sites. Access to an enterprise networks is typically restricted, and may require authorized users to enter a password or otherwise authenticate before using the network. A network such as illustrated by the example enterprise network  400  may also be found at small sites, such as in a small business. 
     The enterprise network  400  may be connected to an external network  450 . The external network  450  may be a public network, such as the Internet. A public network is a network that has been made accessible to any device that can connect to it. A public network may have unrestricted access, meaning that, for example, no password or other authentication is required to connect to it. The external network  450  may include third-party telecommunication lines, such as phone lines, broadcast coaxial cable, fiber optic cables, satellite communications, cellular communications, and the like. The external network  450  may include any number of intermediate network devices, such as switches, routers, gateways, servers, and/or controllers that are not directly part of the enterprise network  400  but that facilitate communication between the network  400  and other network-connected entities, such as a remote site  452 . 
     Remote sites  452  are networks and/or individual computers that are generally located outside the enterprise network  400 , and which may be connected to the enterprise network  400  through intermediate networks, but that function as if within the enterprise network  400  and connected directly to it. For example, an employee may connect to the enterprise network  400  while at home, using various secure protocols, and/or by connecting to a Virtual Private Network (VPN) provided by the enterprise network  400 . While the employee&#39;s computer is connected, the employee&#39;s home is a remote site  452 . Alternatively or additionally, the enterprise network&#39;s  400  owner may have a satellite office with a small internal network. This satellite office&#39;s network may have a fixed connection to the enterprise network  400  over various intermediate networks. This satellite office can also be considered a remote site. 
     The enterprise network  400  may be connected to the external network  450  using a gateway device  404 . The gateway device  404  may include a firewall or similar system for preventing unauthorized access while allowing authorized access to the enterprise network  400 . Examples of gateway devices include routers, modems (e.g. cable, fiber optic, dial-up, etc.), and the like. 
     The gateway device  404  may be connected to a switch  406   a.  The switch  406   a  provides connectivity between various devices in the enterprise network  400 . In this example, the switch  406   a  connects together the gateway device  404 , various servers  408 ,  412 ,  414 ,  416 ,  418 , an another switch  406   b.  A switch typically has multiple ports, and functions to direct packets received on one port to another port. In some implementations, the gateway device  404  and the switch  406   a  may be combined into a single device. 
     Various servers may be connected to the switch  406   a.  For example, a print server  408  may be connected to the switch  406   a.  The print server  408  may provide network access to a number of printers  410 . Client devices connected to the enterprise network  400  may be able to access one of the printers  410  through the printer server  408 . 
     Other examples of servers connected to the switch  406   a  include a file server  412 , database server  414 , and email server  416 . The file server  412  may provide storage for and access to data. This data may be accessible to client devices connected to the enterprise network  400 . The database server  414  may store one or more databases, and provide services for accessing the databases. The email server  416  may host an email program or service, and may also store email for users on the enterprise network  400 . 
     As yet another example, a server rack  418  may be connected to the switch  406 . The server rack  418  may house one or more rack-mounted servers. The server rack  418  may have one connection to the switch  406   a,  or may have multiple connections to the switch  406   a.  The servers in the server rack  418  may have various purposes, including providing computing resources, file storage, database storage and access, and email, among others. 
     An additional switch  406   b  may also be connected to the first switch  406   a.  The additional switch  406   b  may be provided to expand the capacity of the network. A switch typically has a limited number of ports (e.g., 8, 16, 32, 64 or more ports). In most cases, however, a switch can direct traffic to and from another switch, so that by connecting the additional switch  406   b  to the first switch  406   a,  the number of available ports can be expanded. 
     In this example, a server  420  is connected to the additional switch  406   b.  The server  420  may manage network access for a number of network devices or client devices. For example, the server  420  may provide network authentication, arbitration, prioritization, load balancing, and other management services as needed to manage multiple network devices accessing the enterprise network  400 . The server  420  may be connected to a hub  422 . The hub  422  may include multiple ports, each of which may provide a wired connection for a network or client device. A hub is typically a simpler device than a switch, and may be used when connecting a small number of network devices together. In some cases, a switch can be substituted for the hub  422 . In this example, the hub  422  connects desktop computers  424  and laptop computers  426  to the enterprise network  400 . In this example, each of the desktop computers  424  and laptop computers  426  are connected to the hub  422  using a physical cable. 
     In this example, the additional switch  406   b  is also connected to a wireless access point  428 . The wireless access point  428  provides wireless access to the enterprise network  400  for wireless-enabled network or client devices. Examples of wireless-enabled network and client devices include laptops  430 , tablet computers  432 , and smart phones  434 , among others. In some implementations, the wireless access point  428  may also provide switching and/or routing functionality. 
     The example enterprise network  400  of  FIG. 4  is defended from network threats by a network threat detection and analysis system, which uses deception security mechanisms to attract and divert attacks on the network. The deceptive security mechanisms may be controlled by and inserted into the enterprise network  400  using a deception center  498  and sensors  490 , which may also be referred to as deception sensors, installed in various places in the enterprise network  400 . In some implementations, the deception center  498  and the sensors  490  interact with a security services provider  496  located outside of the enterprise network  400 . The deception center  498  may also obtain or exchange data with sources located on external networks  450 , such as the Internet. 
     In various implementations, the sensors  490  are a minimal combination of hardware and/or software, sufficient to form a network connection with the enterprise network  400  and a network tunnel  480  with the deception center  498 . For example, a sensor  490  may be constructed using a low-power processor, a network interface, and a simple operating system. In some implementations, any of the devices in the enterprise network (e.g., the servers  408 ,  412 ,  416 ,  418  the printers  410 , the computing devices  424 ,  426 ,  430 ,  432 ,  434 , or the network infrastructure devices  404 ,  406   a,    406   b,    428 ) can be configured to act as a sensor. 
     In various implementations, one or more sensors  490  can be installed anywhere in the enterprise network  400 , include being attached switches  406   a,  hubs  422 , wireless access points  428 , and so on. The sensors  490  can further be configured to be part of one or more VLANs. The sensors  490  provide the deception center  498  with visibility into the enterprise network  400 , such as for example being able to operate as a node in the enterprise network  400 , and/or being able to present or project deceptive security mechanisms into the enterprise network  400 . Additionally, in various implementations, the sensors  490  may provide a portal through which a suspected attack on the enterprise network  400  can be redirected to the deception center  498 . 
     The deception center  498  provides network security for the enterprise network  400  by deploying security mechanisms into the enterprise network  400 , monitoring the enterprise network  400  through the security mechanisms, detecting and redirecting apparent threats, and analyzing network activity resulting from the apparent threat. To provide security for the enterprise network  400 , in various implementations the deception center  498  may communicate with sensors  490  installed in the enterprise network  400 , using, for example, network tunnels  480 . The tunnels  480  may allow the deception center  498  to be located in a different sub-network (“subnet”) than the enterprise network  400 , on a different network, or remote from the enterprise network  400 , with intermediate networks between the deception center  498  and the enterprise network  400 . In some implementations, the enterprise network  400  can include more than one deception center  498 . In some implementations, the deception center may be located off-site, such as in an external network  450 . 
     In some implementations, the security services provider  496  may act as a central hub for providing security to multiple site networks, possibly including site networks controlled by different organizations. For example, the security services provider  496  may communicate with multiple deception centers  498  that each provide security for a different enterprise network  400  for the same organization. As another example, the security services provider  496  may coordinate the activities of the deception center  498  and the sensors  490 , such as enabling the deception center  498  and the sensors  490  to connect to each other. In some implementations, the security services provider  496  is located outside the enterprise network  400 . In some implementations, the security services provider  496  is controlled by a different entity than the entity that controls the site network. For example, the security services provider  496  may be an outside vendor. In some implementations, the security services provider  496  is controlled by the same entity as that controls the enterprise network  400 . In some implementations, the network security system does not include a security services provider  496 . 
       FIG. 4  illustrates one example of what can be considered a “traditional” network, that is, a network that is based on the interconnection of computers. In various implementations, a network security system, such as the deception-based system discussed above, can also be used to defend “non-traditional” networks that include devices other than traditional computers, such as for example mechanical, electrical, or electromechanical devices, sensors, actuators, and control systems. Such “non-traditional” networks may be referred to as the Internet of Things (IoT). The Internet of Things encompasses newly-developed, every-day devices designed to be networked (e.g., drones, self-driving automobiles, etc.) as well as common and long-established machinery that has augmented to be connected to a network (e.g., home appliances, traffic signals, etc.). 
       FIG. 5  illustrates a general example of an IoT network  500 . The example IoT network  500  can be implemented wherever sensors, actuators, and control systems can be found. For example, the example IoT network  500  can be implemented for buildings, roads and bridges, agriculture, transportation and logistics, utilities, air traffic control, factories, and private homes, among others. In various implementations, the IoT network  500  includes cloud service  554  that collects data from various sensors  510   a - 510   d,    512   a - 512   d,  located in various locations. Using the collected data, the cloud service  554  can provide services  520 , control of machinery and equipment  514 , exchange of data with traditional network devices  516 , and/or exchange of data with user devices  518 . In some implementations, the cloud service  554  can work with a deception center  528  and/or a security service provider  526  to provide security for the network  500 . 
     A cloud service, such as the illustrated cloud service  554 , is a resource provided over the Internet  550 . Sometimes synonymous with “cloud computing,” the resource provided by the cloud services is in the “cloud” in that the resource is provided by hardware and/or software at some location remote from the place where the resource is used. Often, the hardware and software of the cloud service is distributed across multiple physical locations. Generally, the resource provided by the cloud service is not directly associated with specific hardware or software resources, such that use of the resource can continue when the hardware or software is changed. The resource provided by the cloud service can often also be shared between multiple users of the cloud service, without affecting each user&#39;s use. The resource can often also be provided as needed or on-demand. Often, the resource provided by the cloud service  554  is automated, or otherwise capable of operating with little or no assistance from human operators. 
     Examples of cloud services include software as a service (SaaS), infrastructure as a service (IaaS), platform as a service (PaaS), desktop as a service (DaaS), managed software as a service (MSaaS), mobile backend as a service (MBaaS), and information technology management as a service (ITMaas). Specific examples of cloud services include data centers, such as those operated by Amazon Web Services and Google Web Services, among others, that provide general networking and software services. Other examples of cloud services include those associated with smartphone applications, or “apps,” such as for example apps that track fitness and health, apps that allow a user to remotely manage her home security system or thermostat, and networked gaming apps, among others. In each of these examples, the company that provides the app may also provide cloud-based storage of application data, cloud-based software and computing resources, and/or networking services. In some cases, the company manages the cloud services provided by the company, including managing physical hardware resources. In other cases, the company leases networking time from a data center provider. 
     In some cases, the cloud service  554  is part of one integrated system, run by one entity. For example, the cloud service  554  can be part of a traffic control system. In this example, sensors  510   a - 510   d,    512   a - 512   d  can be used to monitor traffic and road conditions. In this example, the cloud service  554  can attempt to optimize the flow of traffic and also provide traffic safety. For example, the sensors  510   a - 510   d,    512   a - 512   d  can include a sensor  512   a  on a bridge that monitors ice formation. When the sensor  512   a  detects that ice has formed on the bridge, the sensor  512   a  can alert the cloud service  554 . The cloud service  554 , can respond by interacting with machinery and equipment  514  that manages traffic in the area of the bridge. For example, the cloud service  554  can turn on warning signs, indicating to drivers that the bridge is icy. Generally, the interaction between the sensor  512 , the cloud service  554 , and the machinery and equipment  514  is automated, requiring little or no management by human operators. 
     In various implementations, the cloud service  554  collects or receives data from sensors  510   a - 510   d,    512   a - 512   d,  distributed across one or more networks. The sensors  510   a - 510   d,    512   a - 512   d  include devices capable of “sensing” information, such as air or water temperature, air pressure, weight, motion, humidity, fluid levels, noise levels, and so on. The sensors  510   a - 510   d,    512   a - 512   d  can alternatively or additionally include devices capable of receiving input, such as cameras, microphones, touch pads, keyboards, key pads, and so on. In some cases, a group of sensors  510   a - 510   d  may be common to one customer network  502 . For example, the sensors  510   a - 510   d  may be motion sensors, traffic cameras, temperature sensors, and other sensors for monitoring traffic in a city&#39;s metro area. In this example, the sensors  510   a - 510   d  can be located in one area of the city, or be distribute across the city, and be connected to a common network. In these cases, the sensors  510   a - 510   d  can communicate with a gateway device  562 , such as a network gateway. The gateway device  562  can further communicate with the cloud service  554 . 
     In some cases, in addition to receiving data from sensors  510   a - 510   d  in one customer network  502 , the cloud service  554  can also receive data from sensors  512   a - 512   d  in other sites  504   a - 504   c.  These other sites  504   a - 504   c  can be part of the same customer network  502  or can be unrelated to the customer network  502 . For example, the other sites  504   a - 504   c  can each be the metro area of a different city, and the sensors  512   a - 512   d  can be monitoring traffic for each individual city. 
     Generally, communication between the cloud service  554  and the sensors  510   a - 510   d,    512   a - 512   d  is bidirectional. For example, the sensors  510   a - 510   d,    512   a - 512   d  can send information to the cloud service  554 . The cloud service  554  can further provide configuration and control information to the sensors  510   a - 510   d,    512   a - 512   d.  For example, the cloud service  554  can enable or disable a sensor  510   a - 510   d,    512   a - 512   d  or modify the operation of a sensor  510   a - 510   d,    512   a - 512   d,  such as changing the format of the data provided by a sensor  510   a - 510   d,    512   a - 512   d  or upgrading the firmware of a sensor  510   a - 510   d,    512   a - 512   d.    
     In various implementations, the cloud service  554  can operate on the data received from the sensors  510   a - 510   d,    512   a - 512   d,  and use this data to interact with services  520  provided by the cloud service  554 , or to interact with machinery and equipment  514 , network devices  516 , and/or user devices  518  available to the cloud service  554 . Services  520  can include software-based services, such as cloud-based applications, website services, or data management services. Services  520  can alternatively or additionally include media, such as streaming video or music or other entertainment services. Services  520  can also include delivery and/or coordination of physical assets, such as for example package delivery, direction of vehicles for passenger pick-up and drop-off, or automate re-ordering and re-stocking of supplies. In various implementations, services  520  may be delivered to and used by the machinery and equipment  514 , the network devices  516 , and/or the user devices  518 . 
     In various implementations, the machinery and equipment  514  can include physical systems that can be controlled by the cloud service  554 . Examples of machinery and equipment  514  include factory equipment, trains, electrical street cars, self-driving cars, traffic lights, gate and door locks, and so on. In various implementations, the cloud service  554  can provide configuration and control of the machinery and equipment  514  in an automated fashion. 
     The network devices  516  can include traditional networking equipment, such as server computers, data storage devices, routers, switches, gateways, and so on. In various implementations, the cloud service  554  can provide control and management of the network devices  516 , such as for example automated upgrading of software, security monitoring, or asset tracking. Alternatively or additionally, in various implementations the cloud service  554  can exchange data with the network devices  516 , such as for example providing websites, providing stock trading data, or providing online shopping resources, among others. Alternatively or additionally, the network devices  516  can include computing systems used by the cloud service provider to manage the cloud service  554 . 
     The user devices  518  can include individual personal computers, smart phones, tablet devices, smart watches, fitness trackers, medical devices, and so on that can be associated with an individual user. The cloud service  554  can exchange data with the user devices  518 , such as for example provide support for applications installed on the user devices  518 , providing websites, providing streaming media, providing directional navigation services, and so on. Alternatively or additionally, the cloud service  554  may enable a user to use a user device  518  to access and/or view other devices, such as the sensors  510   a - 510   d,    512   a - 512   d,  the machinery and equipment  514 , or the network devices  516 . 
     In various implementations, the services  520 , machinery and equipment  514 , network devices  516 , and user devices  518  may be part of one customer network  506 . In some cases, this customer network  506  is the same as the customer network  502  that includes the sensors  510   a - 510   d.  In some cases, the services  520 , machinery and equipment  514 , network devices  516 , and user devices  518  are part of the same network, and may instead be part of various other networks  506 . 
     In various implementations, customer networks can include a deception center  598 . The deception center  598  provides network security for the IoT network  500  by deploying security mechanisms into the IoT network  500 , monitoring the IoT network  500  through the security mechanisms, detecting and redirecting apparent threats, and analyzing network activity resulting from the apparent threat. To provide security for the IoT network  500 , in various implementations the deception center  598  may communicate with the sensors  510   a - 5106   d,    512   a - 5012  installed in the IoT network  500 , for example through the cloud service  554 . In some implementations, the IoT network  500  can include more than one deception center  598 . For example, each of customer network  502  and customer networks or other networks  506  can include a deception center  528 . 
     In some implementations, the deception center  598  and the sensors  510   a - 510   d,    512   a - 512   d  interact with a security services provider  596 . In some implementations, the security services provider  596  may act as a central hub for providing security to multiple site networks, possibly including site networks controlled by different organizations. For example, the security services provider  596  may communicate with multiple deception centers  598  that each provide security for a different IoT network  500  for the same organization. As another example, the security services provider  596  may coordinate the activities of the deception center  598  and the sensors  510   a - 510   d,    512   a - 512   d,  such as enabling the deception center  598  and the sensors  510   a - 510   d,    512   a - 512   d  to connect to each other. In some implementations, the security services provider  596  is integrated into the cloud service  554 . In some implementations, the security services provider  596  is controlled by a different entity than the entity that controls the site network. For example, the security services provider  596  may be an outside vendor. In some implementations, the security services provider  596  is controlled by the same entity as that controls the IoT network  500 . In some implementations, the network security system does not include a security services provider  596 . 
     IoT networks can also include small networks of non-traditional devices.  FIG. 6  illustrates an example of a customer network that is a small network  600 , here implemented in a private home. A network for a home is an example of small network that may have both traditional and non-traditional network devices connected to the network  600 , in keeping with an Internet of Things approach. Home networks are also an example of networks that are often implemented with minimal security. The average homeowner is not likely to be a sophisticated network security expert, and may rely on his modem or router to provide at least some basic security. The homeowner, however, is likely able to at least set up a basic home network. A deception-based network security device may be as simple to set up as a home router or base station, yet provide sophisticated security for the network  600 . 
     The example network  600  of  FIG. 6  may be a single network, or may include multiple sub-networks. These sub-networks may or may not communicate with each other. For example, the network  600  may include a sub-network that uses the electrical wiring in the house as a communication channel. Devices configured to communicate in this way may connect to the network using electrical outlets, which also provide the devices with power. The sub-network may include a central controller device, which may coordinate the activities of devices connected to the electrical network, including turning devices on and off at particular times. One example of a protocol that uses the electrical wiring as a communication network is X10. 
     The network  600  may also include wireless and wired networks, built into the home or added to the home solely for providing a communication medium for devices in the house. Examples of wireless, radio-based networks include networks using protocols such as Z-Wave™, Zigbee™ (also known as Institute of Electrical and Electronics Engineers (IEEE) 802.15.4), Bluetooth™, and Wi-Fi (also known as IEEE 802.11), among others. Wireless networks can be set up by installing a wireless base station in the house. Alternatively or additionally, a wireless network can be established by having at least two devices in the house that are able to communicate with each other using the same protocol. 
     Examples of wired networks include Ethernet (also known as IEEE 802.3), token ring (also known as IEEE 802.5), Fiber Distributed Data Interface (FDDI), and Attached Resource Computer Network (ARCNET), among others. A wired network can be added to the house by running cabling through the walls, ceilings, and/or floors, and placing jacks in various rooms that devices can connect to with additional cables. The wired network can be extended using routers, switches, and/or hubs. In many cases, wired networks may be interconnected with wireless networks, with the interconnected networks operating as one seamless network. For example, an Ethernet network may include a wireless base station that provides a Wi-Fi signal for devices in the house. 
     As noted above, a small network  600  implemented in a home is one that may include both traditional network devices and non-traditional, everyday electronics and appliances that have also been connected to the network  600 . Examples of rooms where one may find non-traditional devices connected to the network are the kitchen and laundry rooms. For example, in the kitchen a refrigerator  604 , oven  606 , microwave  608 , and dishwasher  610  may be connected to the network  600 , and in the laundry room a washing machine  612  may be connected to the network  600 . By attaching these appliances to the network  600 , the homeowner can monitor the activity of each device (e.g., whether the dishes are clean, the current state of a turkey in the oven, or the washing machine cycle) or change the operation of each device without needing to be in the same room or even be at home. The appliances can also be configured to resupply themselves. For example, the refrigerator  604  may detect that a certain product is running low, and may place an order with a grocery delivery service for the product to be restocked. 
     The network  600  may also include environmental appliances, such as a thermostat  602  and a water heater  614 . By having these devices connected to the network  600 , the homeowner can monitor the current environment of the house (e.g., the air temperature or the hot water temperature), and adjust the settings of these appliances while at home or away. Furthermore, software on the network  600  or on the Internet  650  may track energy usage for the heating and cooling units and the water heater  614 . This software may also track energy usage for the other devices, such as the kitchen and laundry room appliances. The energy usage of each appliance may be available to the homeowner over the network  600 . 
     In the living room, various home electronics may be on the network  600 . These electronics may have once been fully analog or may have been standalone devices, but now include a network connection for exchanging data with other devices in the network  600  or with the Internet  650 . The home electronics in this example include a television  618 , a gaming system  620 , and a media device  622  (e.g., a video and/or audio player). Each of these devices may play media hosted, for example, on network attached storage  636  located elsewhere in the network  600 , or media hosted on the Internet  650 . 
     The network  600  may also include home safety and security devices, such as a smoke detector  616 , an electronic door lock  624 , and a home security system  626 . Having these devices on the network may allow the homeowner to track the information monitored and/or sensed by these devices, both when the homeowner is at home and away from the house. For example, the homeowner may be able to view a video feed from a security camera  628 . When the safety and security devices detect a problem, they may also inform the homeowner. For example, the smoke detector  616  may send an alert to the homeowner&#39;s smartphone when it detects smoke, or the electronic door lock  624  may alert the homeowner when there has been a forced entry. Furthermore, the homeowner may be able to remotely control these devices. For example, the homeowner may be able to remotely open the electronic door lock  624  for a family member who has been locked out. The safety and security devices may also use their connection to the network to call the fire department or police if necessary. 
     Another non-traditional device that may be found in the network  600  is the family car  630 . The car  630  is one of many devices, such as laptop computers  638 , tablet computers  646 , and smartphones  642 , that connect to the network  600  when at home, and when not at home, may be able to connect to the network  600  over the Internet  650 . Connecting to the network  600  over the Internet  650  may provide the homeowner with remote access to his network. The network  600  may be able to provide information to the car  630  and receive information from the car  630  while the car is away. For example, the network  600  may be able to track the location of the car  630  while the car  630  is away. 
     In the home office and elsewhere around the house, this example network  600  includes some traditional devices connected to the network  600 . For example, the home office may include a desktop computer  632  and network attached storage  636 . Elsewhere around the house, this example includes a laptop computer  638  and handheld devices such as a tablet computer  646  and a smartphone  642 . In this example, a person  640  is also connected to the network  600 . The person  640  may be connected to the network  600  wirelessly through personal devices worn by the person  640 , such as a smart watch, fitness tracker, or heart rate monitor. The person  640  may alternatively or additionally be connected to the network  600  through a network-enabled medical device, such as a pacemaker, heart monitor, or drug delivery system, which may be worn or implanted. 
     The desktop computer  632 , laptop computer  638 , tablet computer  646 , and/or smartphone  642  may provide an interface that allows the homeowner to monitor and control the various devices connected to the network. Some of these devices, such as the laptop computer  638 , the tablet computer  646 , and the smartphone  642  may also leave the house, and provide remote access to the network  600  over the Internet  650 . In many cases, however, each device on the network may have its own software for monitoring and controlling only that one device. For example, the thermostat  602  may use one application while the media device  622  uses another, and the wireless network provides yet another. Furthermore, it may be the case that the various sub-networks in the house do not communicate with each other, and/or are viewed and controlled using software that is unique to each sub-network. In many cases, the homeowner may not have one unified and easily understood view of his entire home network  600 . 
     The small network  600  in this example may also include network infrastructure devices, such as a router or switch (not shown) and a wireless base station  634 . The wireless base station  634  may provide a wireless network for the house. The router or switch may provide a wired network for the house. The wireless base station  634  may be connected to the router or switch to provide a wireless network that is an extension of the wired network. The router or switch may be connected to a gateway device  648  that connects the network  600  to other networks, including the Internet  650 . In some cases, a router or switch may be integrated into the gateway device  648 . The gateway device  648  is a cable modem, digital subscriber line (DSL) modem, optical modem, analog modem, or some other device that connects the network  600  to an ISP. The ISP may provide access to the Internet  650 . Typically, a home network only has one gateway device  648 . In some cases, the network  600  may not be connected to any networks outside of the house. In these cases, information about the network  600  and control of devices in the network  600  may not be available when the homeowner is not connected to the network  600 ; that is, the homeowner may not have access to his network  600  over the Internet  650 . 
     Typically, the gateway device  648  includes a hardware and/or software firewall. A firewall monitors incoming and outgoing network traffic and, by applying security rules to the network traffic, attempts to keep harmful network traffic out of the network  600 . In many cases, a firewall is the only security system protecting the network  600 . While a firewall may work for some types of intrusion attempts originating outside the network  600 , the firewall may not block all intrusion mechanisms, particularly intrusions mechanisms hidden in legitimate network traffic. Furthermore, while a firewall may block intrusions originating on the Internet  650 , the firewall may not detect intrusions originating from within the network  600 . For example, an infiltrator may get into the network  600  by connecting to signal from the Wi-Fi base station  634 . Alternatively, the infiltrator may connect to the network  600  by physically connecting, for example, to the washing machine  612 . The washing machine  612  may have a port that a service technician can connect to service the machine. Alternatively or additionally, the washing machine  612  may have a simple Universal Serial Bus (USB) port. Once an intruder has gained access to the washing machine  612 , the intruder may have access to the rest of the network  600 . 
     To provide more security for the network  600 , a deception-based network security device  660  can be added to the network  600 . In some implementations, the security device  660  is a standalone device that can be added to the network  600  by connecting it to a router or switch. In some implementations, the security device  660  can alternatively or additionally be connected to the network&#39;s  600  wireless sub-network by powering on the security device  660  and providing it with Wi-Fi credentials. The security device  660  may have a touchscreen, or a screen and a keypad, for inputting Wi-Fi credentials. Alternatively or additionally, the homeowner may be able to enter network information into the security device by logging into the security device  660  over a Bluetooth™ or Wi-Fi signal using software on a smartphone, tablet, or laptop, or using a web browser. In some implementations, the security device  660  can be connected to a sub-network running over the home&#39;s electrical wiring by connecting the security device  660  to a power outlet. In some implementations, the security device  660  may have ports, interfaces, and/or radio antennas for connecting to the various sub-networks that can be included in the network  600 . This may be useful, for example, when the sub-networks do not communicate with each other, or do not communicate with each other seamlessly. Once powered on and connected, the security device  660  may self-configure and monitor the security of each sub-network in the network  600  that it is connected to. 
     In some implementations, the security device  660  may be configured to connect between the gateway device  648  and the network&#39;s  600  primary router, and/or between the gateway device  648  and the gateway device&#39;s  648  connection to the wall. Connected in one or both of these locations, the security device  660  may be able to control the network&#39;s  600  connection with outside networks. For example, the security device can disconnect the network  600  from the Internet  650 . 
     In some implementations, the security device  660 , instead of being implemented as a standalone device, may be integrated into one or more of the appliances, home electronics, or computing devices (in this example network  600 ), or in some other device not illustrated here. For example, the security device  660 —or the functionality of the security device  660 —may be incorporated into the gateway device  648  or a desktop computer  632  or a laptop computer  638 . As another example, the security device  660  can be integrated into a kitchen appliance (e.g., the refrigerator  604  or microwave  608 ), a home media device (e.g., the television  618  or gaming system  620 ), or the home security system  626 . In some implementations, the security device  660  may be a printed circuit board that can be added to another device without requiring significant changes to the other device. In some implementations, the security device  660  may be implemented using an Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) that can be added to the electronics of a device. In some implementations, the security device  660  may be implemented as a software module or modules that can run concurrently with the operating system or firmware of a networked device. In some implementations, the security device  660  may have a physical or virtual security barrier that prevents access to it by the device that it is integrated into. In some implementations, the security device&#39;s  660  presence in another device may be hidden from the device into which the security device  660  is integrated. 
     In various implementations, the security device  660  may scan the network  600  to determine which devices are present in the network  600 . Alternatively or additionally, the security device  660  may communicate with a central controller in the network  600  (or multiple central controllers, when there are sub-networks, each with their own central controller) to learn which devices are connected to the network  600 . In some implementations, the security device  660  may undergo a learning period, during which the security device  660  learns the normal activity of the network  600 , such as what time of day appliances and electronics are used, what they are used for, and/or what data is transferred to and from these devices. During the learning period, the security device  660  may alert the homeowner to any unusual or suspicious activity. The homeowner may indicate that this activity is acceptable, or may indicate that the activity is an intrusion. As described below, the security device  660  may subsequently take preventive action against the intrusion. 
     Once the security device  660  has learned the topology and/or activity of the network  600 , the security device  660  may be able to provide deception-based security for the network  600 . In some implementations, the security device  660  may deploy security mechanisms that are configured to emulate devices that could be found in the network  600 . In some implementations, the security device  660  may monitor activity on the network  600 , including watching the data sent between the various devices on the network  600 , and between the devices and the Internet  650 . The security device  660  may be looking for activity that is unusual, unexpected, or readily identifiable as suspect. Upon detecting suspicious activity in the network  600 , the security device  660  may deploy deceptive security mechanisms. 
     In some implementations, the deceptive security mechanisms are software processes running on the security device  660  that emulate devices that may be found in the network  600 . In some implementations, the security device  660  may be assisted in emulating the security devices by another device on the network  600 , such as the desktop computer  632 . From the perspective of devices connected to the network  600 , the security mechanisms appear just like any other device on the network, including, for example, having an Internet Protocol (IP) address, a Media Access Control (MAC) address, and/or some other identification information, having an identifiable device type, and responding to or transmitting data just as would the device being emulated. The security mechanisms may be emulated by the security device  660  itself; thus, while, from the point of view of the network  600 , the network  600  appears to have additional devices, no physical equivalent (other than the security device  660 ) can be found in the house. 
     The devices and data emulated by a security mechanism are selected such that the security mechanism is an attractive target for intrusion attempts. Thus, the security mechanism may emulate valuable data, and/or devices that are easily hacked into, and/or devices that provide easy access to the reset of the network  600 . Furthermore, the security mechanisms emulate devices that are likely to be found in the network  600 , such as a second television, a second thermostat, or another laptop computer. In some implementations, the security device  660  may contact a service on the Internet  650  for assistance in selecting devices to emulate and/or for how to configure emulated devices. The security devices  660  may select and configure security mechanisms to be attractive to intrusions attempts, and to deflect attention away from more valuable or vulnerable network assets. Additionally, the security mechanisms can assist in confirming that an intrusion into the network  600  has actually taken place. 
     In some implementations, the security device  660  may deploy deceptive security mechanisms in advance of detecting any suspicious activity. For example, having scanned the network, the security device  660  may determine that the network  600  includes only one television  618  and one smoke detector  616 . The security device  660  may therefore choose to deploy security mechanisms that emulate a second television and a second smoke detector. With security mechanisms preemptively added to the network, when there is an intrusion attempt, the intruder may target the security mechanisms instead of valuable or vulnerable network devices. The security mechanisms thus may serve as decoys and may deflect an intruder away from the network&#39;s  600  real devices. 
     In some implementations, the security mechanisms deployed by the security device  660  may take into account specific requirements of the network  600  and/or the type of devices that can be emulated. For example, in some cases, the network  600  (or a sub-network) may assign identifiers to each device connected to the network  600 , and/or each device may be required to adopt a unique identifier. In these cases, the security device  660  may assign an identifier to deployed security mechanisms that do not interfere with identifiers used by actual devices in the network  600 . As another example, in some cases, devices on the network  600  may register themselves with a central controller and/or with a central service on the Internet  650 . For example, the thermostat  602  may register with a service on the Internet  650  that monitors energy use for the home. In these cases, the security mechanisms that emulate these types of devices may also register with the central controller or the central service. Doing so may improve the apparent authenticity of the security mechanism, and may avoid conflicts with the central controller or central service. Alternatively or additionally, the security device  660  may determine to deploy security mechanisms that emulate other devices, and avoid registering with the central controller or central service. 
     In some implementations, the security device  660  may dynamically adjust the security mechanisms that it has deployed. For example, when the homeowner adds devices to the network  600 , the security device  660  may remove security mechanisms that conflict with the new devices, or change a security mechanism so that the security mechanism&#39;s configuration is not incongruous with the new devices (e.g., the security mechanisms should not have the same MAC address as a new device). As another example, when the network owner removes a device from the network  600 , the security device  660  may add a security mechanism that mimics the device that was removed. As another example, the security device may change the activity of a security mechanism, for example, to reflect changes in the normal activity of the home, changes in the weather, the time of year, the occurrence of special events, and so on. 
     The security device  660  may also dynamically adjust the security mechanisms it has deployed in response to suspicious activity it has detected on the network  600 . For example, upon detecting suspicious activity, the security device  660  may change the behavior of a security mechanism or may deploy additional security mechanisms. The changes to the security mechanisms may be directed by the suspicious activity, meaning that if, for example, the suspicious activity appears to be probing for a wireless base station  634 , the security device  660  may deploy a decoy wireless base station. 
     Changes to the security mechanisms are meant not only to attract a possible intrusion, but also to confirm that an intrusion has, in fact occurred. Since the security mechanisms are not part of the normal operation of the network  600 , normal occupants of the home are not expected to access the security mechanisms. Thus, in most cases, any access of a security mechanism is suspect. Once the security device  660  has detected an access to a security mechanism, the security device  660  may next attempt to confirm that an intrusion into the network  600  has taken place. An intrusion can be confirmed, for example, by monitoring activity at the security mechanism. For example, login attempts, probing of data emulated by the security mechanism, copying of data from the security mechanism, and attempts to log into another part of the network  600  from the security mechanism indicate a high likelihood that an intrusion has occurred. 
     Once the security device  660  is able to confirm an intrusion into the network  600 , the security device  660  may alert the homeowner. For example, the security device  660  may sound an audible alarm, send an email or text message to the homeowner or some other designated persons, and/or send an alert to an application running on a smartphone or tablet. As another example, the security device  660  may access other network devices and, for example, flash lights, trigger the security system&#39;s  626  alarm, and/or display messages on devices that include display screens, such as the television  618  or refrigerator  604 . In some implementations, depending on the nature of the intrusion, the security device  660  may alert authorities such as the police or fire department. 
     In some implementations, the security device  660  may also take preventive actions. For example, when an intrusion appears to have originated outside the network  600 , the security device  660  may block the network&#39;s  600  access to the Internet  650 , thus possibly cutting off the intrusion. As another example, when the intrusion appears to have originated from within the network  600 , the security device  660  may isolate any apparently compromised devices, for example by disconnecting them from the network  600 . When only its own security mechanisms are compromised, the security device  660  may isolate itself from the rest of the network  600 . As another example, when the security device  660  is able to determine that the intrusion very likely included physical intrusion into the house, the security device  660  may alert the authorities. The security device  660  may further lock down the house by, for example, locking any electronic door locks  624 . 
     In some implementations, the security device  660  may be able to enable a homeowner to monitor the network  600  when a suspicious activity has been detected, or at any other time. For example, the homeowner may be provided with a software application that can be installed on a smartphone, tablet, desktop, and/or laptop computer. The software application may receive information from the security device  660  over a wired or wireless connection. Alternatively or additionally, the homeowner may be able to access information about his network through a web browser, where the security device  660  formats webpages for displaying the information. Alternatively or additionally, the security device  660  may itself have a touchscreen or a screen and key pad that provide information about the network  600  to the homeowner. 
     The information provided to the homeowner may include, for example, a list and/or graphic display of the devices connected to the network  600 . The information may further provide a real-time status of each device, such as whether the device is on or off, the current activity of the device, data being transferred to or from the device, and/or the current user of the device, among other things. The list or graphic display may update as devices connect and disconnect from the network  600 , such as for example laptops and smartphones connecting to or disconnecting from a wireless sub-network in the network  600 . The security device  660  may further alert the homeowner when a device has unexpectedly been disconnected from the network  600 . The security device  660  may further alert the homeowner when an unknown device connects to the network  600 , such as for example when a device that is not known to the homeowner connects to the Wi-Fi signal. 
     The security device  660  may also maintain historic information. For example, the security device  660  may provide snapshots of the network  600  taken once a day, once a week, or once a month. The security device  660  may further provide a list of devices that have, for example, connected to the wireless signal in the last hour or day, at what times, and for how long. The security device  660  may also be able to provide identification information for these devices, such as MAC addresses or usernames. As another example, the security device  660  may also maintain usage statistics for each device in the network  600 , such as for example the times at which each device was in use, what the device was used for, how much energy the device used, and so on. 
     The software application or web browser or display interface that provides the homeowner with information about his network  600  may also enable the homeowner to make changes to the network  600  or to devices in the network  600 . For example, through the security device  660 , the homeowner may be able to turn devices on or off, change the configuration of a device, change a password for a device or for the network, and so on. 
     In some implementations, the security device  660  may also display currently deployed security mechanisms and their configuration. In some implementations, the security device  660  may also display activity seen at the security mechanisms, such as for example a suspicious access to a security mechanism. In some implementations, the security device  660  may also allow the homeowner to customize the security mechanisms. For example, the homeowner may be able to add or remove security mechanisms, modify data emulated by the security mechanisms, modify the configuration of security mechanism, and/or modify the activity of a security mechanism. 
     A deception-based network security device  660  thus can provide sophisticated security for a small network. The security device  660  may be simple to add to a network, yet provide comprehensive protection against both external and internal intrusions. Moreover, the security device  660  may be able to monitor multiple sub-networks that are each using different protocols. The security device  660 , using deceptive security mechanisms, may be able to detect and confirm intrusions into the network  600 . The security device  660  may be able to take preventive actions when an intrusion occurs. The security device  660  may also be able to provide the homeowner with information about his network, and possibly also control over devices in the network. 
       FIG. 7  illustrates another example of a small network  700 , here implemented in a small business. A network in a small business may have both traditional and non-traditional devices connected to the network  700 . Small business networks are also examples of networks that are often implemented with minimal security. A small business owner may not have the financial or technical resources, time, or expertise to configure a sophisticated security infrastructure for her network  700 . The business owner, however, is likely able to at least set up a network  700  for the operation of the business. A deception-based network security device that is at least as simple to set up as the network  700  itself may provide inexpensive and simple yet sophisticated security for the network  700 . 
     The example network  700  may be one, single network, or may include multiple sub-networks. For example, the network  700  may include a wired sub-network, such as an Ethernet network, and a wireless sub-network, such as an 802.11 Wi-Fi network. The wired sub-network may be implemented using cables that have been run through the walls and/or ceilings to the various rooms in the business. The cables may be connected to jacks in the walls that devices can connect to in order to connect to the network  700 . The wireless network may be implemented using a wireless base station  720 , or several wireless base stations, which provide a wireless signal throughout the business. The network  700  may include other wireless sub-networks, such as a short-distance Bluetooth™ network. In some cases, the sub-networks communicate with one another. For example, the Wi-Fi sub-network may be connected to the wired Ethernet sub-network. In some cases, the various sub-networks in the network  700  may not be configured to or able to communicate with each other. 
     As noted above, the small business network  700  may include both computers, network infrastructure devices, and other devices not traditionally found in a network. The network  700  may also include electronics, machinery, and systems that have been connected to the network  700  according to an Internet-of-Things approach. Workshop machinery that was once purely analog may now have computer controls. Digital workshop equipment may be network-enabled. By connecting shop equipment and machinery to the network  700 , automation and efficiency of the business can be improved and orders, materials, and inventory can be tracked. Having more devices on the network  700 , however, may increase the number of vulnerabilities in the network  700 . Devices that have only recently become network-enabled may be particularly vulnerable because their security systems have not yet been hardened through use and attack. A deception-based network security device may provide simple-to-install and sophisticated security for a network that may otherwise have only minimal security. 
     The example small business of  FIG. 7  includes a front office. In the front office, the network may include devices for administrative tasks. These devices may include, for example, a laptop computer  722  and a telephone  708 . These devices may be attached to the network  700  in order to, for example, access records related to the business, which may be stored on a server  732  located elsewhere in the building. In the front office, security devices for the building may also be found, including, for example, security system controls  724  and an electronic door lock  726 . Having the security devices on the network  700  may enable the business owner to remotely control access to the building. The business owner may also be able to remotely monitor the security of building, such as for example being able to view video streams from security cameras  742 . The front office may also be where environmental controls, such as a thermostat  702 , are located. Having the thermostat  702  on the network  700  may allow the business owner to remotely control the temperature settings. A network-enabled thermostat  702  may also track energy usage for the heating and cooling systems. The front office may also include safety devices, such as a network-connected smoke alarm  728 . A network-connected smoke alarm may be able to inform the business owner that there is a problem in the building be connecting to the business owner&#39;s smartphone or computer. 
     Another workspace in this example small business is a workshop. In the workshop, the network  700  may include production equipment for producing the goods sold by the business. The production equipment may include, for example, manufacturing machines  704  (e.g. a milling machine, a Computer Numerical Control (CNC) machine, a 3D printer, or some other machine tool) and a plotter  706 . The production equipment may be controlled by a computer on the network  700 , and/or may receive product designs over the network  700  and independently execute the designs. In the workshop, one may also find other devices related to the manufacturing of products, such as radiofrequency identification (RFID) scanners, barcode or Quick Response (QR) code generators, and other devices for tracking inventory, as well as electronic tools, hand tools, and so on. 
     In the workshop and elsewhere in the building, mobile computing devices and people  738  may also be connected to the network  700 . Mobile computing devices include, for example, tablet computers  734  and smartphones  736 . These devices may be used to control production equipment, track supplies and inventory, receive and track orders, and/or for other operations of the business. People  738  may be connected to the network through network-connected devices worn or implanted in the people  738 , such as for example smart watches, fitness trackers, heart rate monitors, drug delivery systems, pacemakers, and so on. 
     At a loading dock, the example small business may have a delivery van  748  and a company car  746 . When these vehicles are away from the business, they may be connected to the network  700  remotely, for example over the Internet  750 . By being able to communicate with the network  700 , the vehicles may be able to receive information such as product delivery information (e.g., orders, addresses, and/or delivery times), supply pickup instructions, and so on. The business owner may also be able to track the location of these vehicles from the business location, or over the Internet  750  when away from the business, and/or track who is using the vehicles. 
     The business may also have a back office. In the back office, the network  700  may include traditional network devices, such as computers  730 , a multi-function printer  716 , a scanner  718 , and a server  732 . In this example, the computers  730  may be used to design products for manufacturing in the workshop, as well as for management of the business, including tracking orders, supplies, inventory, and/or human resources records. The multi-function printer  716  and scanner  718  may support the design work and the running of the business. The server  732  may store product designs, orders, supply records, and inventory records, as well as administrative data, such as accounting and human resources data. 
     The back office may also be where a gateway device  770  is located. The gateway device  770  connects the small business to other networks, including the Internet  750 . Typically, the gateway device  770  connects to an ISP, and the ISP provides access to the Internet  750 . In some cases, a router may be integrated into the gateway device  770 . In some cases, gateway device  770  may be connected to an external router, switch, or hub, not illustrated here. In some cases, the network  700  is not connected to any networks outside of the business&#39;s own network  700 . In these cases, the network  700  may not have a gateway device  770 . 
     The back office is also where the network  700  may have a deception-based network security device  760 . The security device  760  may be a standalone device that may be enabled as soon as it is connected to the network  700 . Alternatively or additionally, the security device  760  may be integrated into another device connected to the network  700 , such as the gateway device  770 , a router, a desktop computer  730 , a laptop computer  722 , the multi-function printer  716 , or the thermostat  702 , among others. When integrated into another device, the security device  760  may use the network connection of the other device, or may have its own network connection for connecting to the network  700 . The security device  760  may connect to the network  700  using a wired connection or a wireless connection. 
     Once connected to the network  700 , the security device  760  may begin monitoring the network  700  for suspect activity. In some implementations, the security device  760  may scan the network  700  to learn which devices are connected to the network  700 . In some cases, the security device  760  may learn the normal activity of the network  700 , such as what time the various devices are used, for how long, by whom, for what purpose, and what data is transferred to and from each device, among other things. 
     In some implementations, having learned the configuration and/or activity of the network  700 , the security device  760  may deploy deceptive security mechanisms. These security mechanisms may emulate devices that may be found on the network  700 , including having an identifiable device type and/or network identifiers (such as a MAC address and/or IP address), and being able to send and receive network traffic that a device of a certain time would send and receive. For example, for the example small business, the security device  760  may configure a security mechanism to emulate a 3D printer, a wide-body scanner, or an additional security camera. The security device  760  may further avoid configuring a security mechanism to emulate a device that is not likely to be found in the small business, such as a washing machine. The security device  760  may use the deployed security mechanisms to monitor activity on the network  700 . 
     In various implementations, when the security device  760  detects suspect activity, the security device  760  may deploy additional security mechanisms. These additional security mechanisms may be selected based on the nature of suspect activity. For example, when the suspect activity appears to be attempting to break into the shop equipment, the security device  760  may deploy a security mechanism that looks like shop equipment that is easy to hack. In some implementations, the security device  760  may deploy security mechanisms only after detecting suspect activity on the network  700 . 
     The security device  760  selects devices to emulate that are particularly attractive for an infiltration, either because the emulated device appears to have valuable data or because the emulated device appears to be easy to infiltrate, or for some other reason. In some implementations, the security device  760  connects to a service on the Internet  750  for assistance in determining which devices to emulate and/or how to configure the emulated device. Once deployed, the security mechanisms serve as decoys to attract the attention of a possible infiltrator away from valuable network assets. In some implementations, the security device  760  emulates the security mechanisms using software processes. In some implementations, the security device  760  may be assisted in emulating security mechanisms by a computer  730  on the network. 
     In some implementations, the security device  760  may deploy security mechanisms prior to detecting suspicious activity on the network  700 . In these implementations, the security mechanisms may present more attractive targets for a possible, future infiltration, so that if an infiltration occurs, the infiltrator will go after the security mechanisms instead of the actual devices on the network  700 . 
     In various implementations, the security device  760  may also change the security mechanisms that it has deployed. For example, the security device  760  may add or remove security mechanisms as the operation of the business changes, as the activity on the network  700  changes, as devices are added or removed from the network  700 , as the time of year changes, and so on. 
     Besides deflecting a possible network infiltration away from valuable or vulnerable network devices, the security device  760  may use the security mechanisms to confirm that the network  700  has been infiltrated. Because the security mechanisms are not part of actual devices in use by the business, any access to them over the network is suspect. Thus, once the security device  760  detects an access to one of its security mechanisms, the security device  760  may attempt to confirm that this access is, in fact, an unauthorized infiltration of the network  700 . 
     To confirm that a security mechanism has been infiltrated, the security device  760  may monitor activity seen at the security mechanism. The security device  760  may further deploy additional security mechanisms, to see if, for example, it can present an even more attractive target to the possible infiltrator. The security device  760  may further look for certain activity, such as log in attempts to other devices in the network, attempts to examine data on the security mechanism, attempts to move data from the security mechanism to the Internet  750 , scanning of the network  700 , password breaking attempts, and so on. 
     Once the security device  760  has confirmed that the network  700  has been infiltrated, the security device  760  may alert the business owner. For example, the security device  760  may sound an audible alarm, email or send text messages to the computers  730  and/or handheld devices  734 ,  736 , send a message to the business&#39;s cars  746 ,  748 , flash lights, or trigger the security system&#39;s  724  alarm. In some implementations, the security device  760  may also take preventive measures. For example, the security device  760  may disconnect the network  700  from the Internet  750 , may disconnect specific devices from the network  700  (e.g., the server  732  or the manufacturing machines  704 ), may turn some network-connected devices off, and/or may lock the building. 
     In various implementations, the security device  760  may allow the business owner to monitor her network  700 , either when an infiltration is taking place or at any other time. For example, the security device  760  may provide a display of the devices currently connected to the network  700 , including flagging any devices connected to the wireless network that do not appear to be part of the business. The security device  760  may further display what each device is currently doing, who is using them, how much energy each device is presently using, and/or how much network bandwidth each device is using. The security device  760  may also be able to store this information and provide historic configuration and/or usage of the network  700 . 
     The security device  760  may have a display it can use to show information to the business owner. Alternatively or additionally, the security device  760  may provide this information to a software application that can run on a desktop or laptop computer, a tablet, or a smartphone. Alternatively or additionally, the security device  760  may format this information for display through a web browser. The business owner may further be able to control devices on the network  700  through an interface provided by the security device  760 , including, for example, turning devices on or off, adjusting settings on devices, configuring user accounts, and so on. The business owner may also be able to view any security mechanisms presently deployed, and may be able to re-configure the security mechanisms, turn them off, or turn them on. 
     IoT networks can also include industrial control systems. Industrial control system is a general term that encompasses several types of control systems, including supervisory control and data acquisition (SCADA) systems, distributed control systems (DCS) and other control system configurations, such as Programmable Logic Controllers (PLCs), often found in the industrial sectors and infrastructures. Industrial control systems are often found in industries such as electrical, water and wastewater, oil and natural gas, chemical, transportation, pharmaceutical, pulp and paper, food and beverage, and discrete manufacturing (e.g., automotive, aerospace, and durable goods). While a large percentage of industrial control systems may be privately owned and operated, federal agencies also operate many industrial processes, such as air traffic control systems and materials handling (e.g., Postal Service mail handling). 
       FIG. 8  illustrates an example of the basic operation of an industrial control system  800 . Generally, an industrial control system  800  may include a control loop  802 , a human-machine interface  806 , and remote diagnostics and maintenance  808 . In some implementations, the example industrial control system can be defended by a network threat detection and analysis system, which can include a deception center  898  and a security services provider  896 . 
     A control loop  802  may consist of sensors  812 , controller  804  hardware such as PLCs, actuators  810 , and the communication of variables  832 ,  834 . The sensors  812  may be used for measuring variables in the system, while the actuators  810  may include, for example, control valves breakers, switches, and motors. Some of the sensors  812  may be deceptions sensors. Controlled variables  834  may be transmitted to the controller  804  from the sensors  812 . The controller  804  may interpret the controlled variables  834  and generates corresponding manipulated variables  832 , based on set points provided by controller interaction  830 . The controller  804  may then transmit the manipulated variables  832  to the actuators  810 . The actuators  810  may drive a controlled process  814  (e.g., a machine on an assembly line). The controlled process  814  may accept process inputs  822  (e.g., raw materials) and produce process outputs  824  (e.g., finished products). New information  820  provided to the controlled process  814  may result in new sensor  812  signals, which identify the state of the controlled process  814  and which may also transmitted to the controller  804 . 
     In some implementations, at least some of the sensors  812  can also provide the deception center  898  with visibility into the industrial control system  800 , such as for example being able to present or project deceptive security mechanisms into the industrial control system. Additionally, in various implementations, the sensors  812  may provide a portal through which a suspected attack on the industrial control system can be redirected to the deception center  898 . The deception center  898  and the sensors  812  may be able to communicate using network tunnels  880 . 
     The deception center  898  provides network security for the industrial control system  800  by deploying security mechanisms into the industrial control system  800 , monitoring the industrial control system through the security mechanisms, detecting and redirecting apparent threats, and analyzing network activity resulting from the apparent threat. In some implementations, the industrial control system  800  can include more than one deception center  898 . In some implementations, the deception center may be located off-site, such as on the Internet. 
     In some implementations, the deception center  898  may interact with a security services provider  896  located outside the industrial control system  800 . The security services provider  896  may act as a central hub for providing security to multiple sites that are part of the industrial control system  800 , and/or for multiple separate, possibly unrelated, industrial control systems. For example, the security services provider  896  may communicate with multiple deception centers  898  that each provide security for a different industrial control system  800  for the same organization. As another example, the security services provider  896  may coordinate the activities of the deception center  898  and the sensors  812 , such as enabling the deception center  898  and the sensors  812  to connect to each other. In some implementations, the security services provider  896  is located outside the industrial control system  800 . In some implementations, the security services provider  896  is controlled by a different entity than the entity that controls the site network. For example, the security services provider  896  may be an outside vendor. In some implementations, the security services provider  896  is controlled by the same entity as that controls the industrial control system. In some implementations, the network security system does not include a security services provider  896 . 
     The human-machine interface  806  provides operators and engineers with an interface for controller interaction  830 . Controller interaction  830  may include monitoring and configuring set points and control algorithms, and adjusting and establishing parameters in the controller  804 . The human-machine interface  806  typically also receives information from the controller  804  that allows the human-machine interface  806  to display process status information and historical information about the operation of the control loop  802 . 
     The remote diagnostics and maintenance  808  utilities are typically used to prevent, identify, and recover from abnormal operation or failures. For diagnostics, the remote diagnostics and maintenance utilities  808  may monitor the operation of each of the controller  804 , sensors  812 , and actuators  810 . To recover after a problem, the remote diagnostics and maintenance  808  utilities may provide recovery information and instructions to one or more of the controller  804 , sensors  812 , and/or actuators  810 . 
     A typical industrial control system contains many control loops, human-machine interfaces, and remote diagnostics and maintenance tools, built using an array of network protocols on layered network architectures. In some cases, multiple control loops are nested and/or cascading, with the set point for one control loop being based on process variables determined by another control loop. Supervisory-level control loops and lower-level control loops typically operate continuously over the duration of a process, with cycle times ranging from milliseconds to minutes. 
     One type of industrial control system that may include many control loops, human-machine interfaces, and remote diagnostics and maintenance tools is a supervisory control and data acquisition (SCADA) system. SCADA systems are used to control dispersed assets, where centralized data acquisition is typically as important as control of the system. SCADA systems are used in distribution systems such as, for example, water distribution and wastewater collection systems, oil and natural gas pipelines, electrical utility transmission and distribution systems, and rail and other public transportation systems, among others. SCADA systems typically integrate data acquisition systems with data transmission systems and human-machine interface software to provide a centralized monitoring and control system for numerous process inputs and outputs. SCADA systems are typically designed to collect field information, transfer this information to a central computer facility, and to display the information to an operator in a graphic and/or textual manner. Using this displayed information, the operator may, in real time, monitor and control an entire system from a central location. In various implementations, control of any individual sub-system, operation, or task can be automatic, or can be performed by manual commands. 
       FIG. 9  illustrates an example of a SCADA system  900 , here used for distributed monitoring and control. This example SCADA system  900  includes a primary control center  902  and three field sites  930   a - 930   c.  A backup control center  904  provides redundancy in case of there is a malfunction at the primary control center  902 . The primary control center  902  in this example includes a control server  906 —which may also be called a SCADA server or a Master Terminal Unit (MTU)—and a local area network (LAN)  908 . The primary control center  902  may also include a human-machine interface station  908 , a data historian  910 , engineering workstations  912 , and various network equipment such as printers  914 , each connected to the LAN  918 . 
     The control server  906  typically acts as the master of the SCADA system  900 . The control server  906  typically includes supervisory control software that controls lower-level control devices, such as Remote Terminal Units (RTUs) and PLCs, located at the field sites  930   a - 930   c.  The software may tell the system  900  what and when to monitor, what parameter ranges are acceptable, and/or what response to initiate when parameters are outside of acceptable values. 
     The control server  906  of this example may access Remote Terminal Units and/or PLCs at the field sites  930   a - 930   c  using a communications infrastructure, which may include radio-based communication devices, telephone lines, cables, and/or satellites. In the illustrated example, the control server  906  is connected to a modem  916 , which provides communication with serial-based radio communication  920 , such as a radio antenna. Using the radio communication  920 , the control server  906  can communicate with field sites  930   a - 930   b  using radiofrequency signals  922 . Some field sites  930   a - 930   b  may have radio transceivers for communicating back to the control server  906 . 
     A human-machine interface station  908  is typically a combination of hardware and software that allows human operators to monitor the state of processes in the SCADA system  900 . The human-machine interface station  908  may further allow operators to modify control settings to change a control objective, and/or manually override automatic control operations, such as in the event of an emergency. The human-machine interface station  908  may also allow a control engineer or operator to configure set points or control algorithms and parameters in a controller, such as a Remote Terminal Unit or a PLC. The human-machine interface station  908  may also display process status information, historical information, reports, and other information to operators, administrators, mangers, business partners, and other authorized users. The location, platform, and interface of a human-machine interface station  908  may vary. For example, the human-machine interface station  908  may be a custom, dedicated platform in the primary control center  902 , a laptop on a wireless LAN, or a browser on a system connected to the Internet. 
     The data historian  910  in this example is a database for logging all process information within the SCADA system  900 . Information stored in this database can be accessed to support analysis of the system  900 , for example for statistical process control or enterprise level planning. 
     The backup control center  904  may include all or most of the same components that are found in the primary control center  902 . In some cases, the backup control center  904  may temporarily take over for components at the primary control center  902  that have failed or have been taken offline for maintenance. In some cases, the backup control center  904  is configured to take over all operations of the primary control center  902 , such as when the primary control center  902  experiences a complete failure (e.g., is destroyed in a natural disaster). 
     The primary control center  902  may collect and log information gathered by the field sites  930   a - 930   c  and display this information using the human-machine interface station  908 . The primary control center  902  may also generate actions based on detected events. The primary control center  902  may, for example, poll field devices at the field sites  930   a - 930   c  for data at defined intervals (e.g.,  5  or  60  seconds), and can send new set points to a field device as required. In addition to polling and issuing high-level commands, the primary control center  902  may also watch for priority interrupts coming from the alarm systems at the field sites  930   a - 930   c.    
     In this example, the primary control center  902  uses point-to-point connections to communication with three field sites  930   a - 930   c,  using radio telemetry for two communications with two of the field sites  930   a - 930   b.  In this example, the primary control center  902  uses a wide area network (WAN)  960  to communicate with the third field site  930   c.  In other implementations, the primary control center  902  may use other communication topologies to communicate with field sites. Other communication topologies include rings, stars, meshes, trees, lines or series, and busses or multi-drops, among others. Standard and proprietary communication protocols may be used to transport information between the primary control center  902  and field sites  930   a - 930   c.  These protocols may use telemetry techniques such as provided by telephone lines, cables, fiber optics, and/or radiofrequency transmissions such as broadcast, microwave, and/or satellite communications. 
     The field sites  930   a - 930   c  in this example perform local control of actuators and monitor local sensors. For example, a first field site  930   a  may include a PLC  932 . A PLC is a small industrial computer originally designed to perform the logic functions formerly executed by electrical hardware (such as relays, switches, and/or mechanical timers and counters). PLCs have evolved into controllers capable of controlling complex processes, and are used extensively in both SCADA systems and distributed control systems. Other controllers used at the field level include process controllers and Remote Terminal Units, which may provide the same level of control as a PLC but may be designed for specific control applications. In SCADA environments, PLCs are often used as field devices because they are more economical, versatile, flexible, and configurable than special-purpose controllers. 
     The PLC  932  at a field site, such as the first field site  930   a,  may control local actuators  934 ,  936  and monitor local sensors  938 ,  940 ,  942 . Examples of actuators include valves  934  and pumps  936 , among others. Examples of sensors include level sensors  938 , pressure sensors  940 , and flow sensors  942 , among others. Any of the actuators  934 ,  936  or sensors  938 ,  940 ,  942  may be “smart” actuators or sensors, more commonly called intelligent electronic devices (IEDs). Intelligent electronic devices may include intelligence for acquiring data, communicating with other devices, and performing local processing and control. An intelligent electronic device could combine an analog input sensor, analog output, low-level control capabilities, a communication system, and/or program memory in one device. The use of intelligent electronic devices in SCADA systems and distributed control systems may allow for automatic control at the local level. Intelligent electronic devices, such as protective relays, may communicate directly with the control server  906 . Alternatively or additionally, a local Remote Terminal Unit may poll intelligent electronic devices to collect data, which it may then pass to the control server  906 . 
     Field sites  930   a - 930   c  are often equipped with remote access capability that allows field operators to perform remote diagnostics and repairs. For example, the first remote  930   a  may include a modem  916  connected to the PLC  932 . A remote access  950  site may be able to, using a dial up connection, connect to the modem  916 . The remote access  950  site may include its own modem  916  for dialing into to the field site  930   a  over a telephone line. At the remote access  950  site, an operator may use a computer  952  connected to the modem  916  to perform diagnostics and repairs on the first field site  930   a.    
     The example SCADA system  900  includes a second field site  930   b,  which may be provisioned in substantially the same way as the first field site  930   a,  having at least a modem and a PLC or Remote Terminal that controls and monitors some number of actuators and sensors. 
     The example SCADA system  900  also includes a third field site  930   c  that includes a network interface card (NIC)  944  for communicating with the system&#39;s  900  WAN  960 . In this example, the third field site  930   c  includes a Remote Terminal Unit  946  that is responsible for controlling local actuators  934 ,  936  and monitoring local sensors  938 ,  940 ,  942 . A Remote Terminal Unit, also called a remote telemetry unit, is a special-purpose data acquisition and control unit typically designed to support SCADA remote stations. Remote Terminal Units may be field devices equipped with wireless radio interfaces to support remote situations where wire-based communications are unavailable. In some cases, PLCs are implemented as Remote Terminal Units. 
     The SCADA system  900  of this example also includes a regional control center  970  and a corporate enterprise network  980 . The regional control center  970  may provide a higher level of supervisory control. The regional control center  970  may include at least a human-machine interface station  908  and a control server  906  that may have supervisory control over the control server  906  at the primary control center  902 . The corporate enterprise network  980  typically has access, through the system&#39;s  900  WAN  960 , to all the control centers  902 ,  904  and to the field sites  930   a - 930   c.  The corporate enterprise network  980  may include a human-machine interface station  908  so that operators can remotely maintain and troubleshoot operations. 
     Another type of industrial control system is the distributed control system (DCS). Distributed control systems are typically used to control production systems within the same geographic location for industries such as oil refineries, water and wastewater management, electric power generation plants, chemical manufacturing plants, and pharmaceutical processing facilities, among others. These systems are usually process control or discrete part control systems. Process control systems may be processes that run continuously, such as manufacturing processes for fuel or steam flow in a power plant, for petroleum production in a refinery, or for distillation in a chemical plant. Discrete part control systems have processes that have distinct processing steps, typically with a distinct start and end to each step, such as found in food manufacturing, electrical and mechanical parts assembly, and parts machining. Discrete-based manufacturing industries typically conduct a series of steps on a single item to create an end product. 
     A distributed control system typically uses a centralized supervisory control loop to mediate a group of localized controllers that share the overall tasks of carrying out an entire production process. By modularizing the production system, a distributed control system may reduce the impact of a single fault on the overall system. A distributed control system is typically interfaced with a corporate network to give business operations a view of the production process. 
       FIG. 10  illustrates an example of a distributed control system  1000 . This example distributed control system  1000  encompasses a production facility, including bottom-level production processes at a field level  1004 , supervisory control systems at a supervisory level  1002 , and a corporate or enterprise layer. 
     At the supervisory level  1002 , a control server  1006 , operating as a supervisory controller, may communicate with subordinate systems via a control network  1018 . The control server  1006  may send set points to distributed field controllers, and may request data from the distributed field controllers. The supervisory level  1002  may include multiple control servers  1006 , with one acting as the primary control server and the rest acting as redundant, back-up control servers. The supervisory level  1002  may also include a main human-machine interface  1008  for use by operators and engineers, a data historian  1010  for logging process information from the system  1000 , and engineering workstations  1012 . 
     At the field level  1004 , the system  1000  may include various distributed field controllers. In the illustrated example, the distributed control system  1000  includes a machine controller  1020 , a PLC  1032 , a process controller  1040 , and a single loop controller  1044 . The distributed field controllers may each control local process actuators, based on control server  1006  commands and sensor feedback from local process sensors. 
     In this example, the machine controller  1020  drives a motion control network  1026 . Using the motion control network  1026 , the machine controller  1020  may control a number of servo drives  1022 , which may each drive a motor. The machine controller  1020  may also drive a logic control bus  1028  to communicate with various devices  1024 . For example, the machine controller  1020  may use the logic control bus  1028  to communicate with pressure sensors, pressure regulators, and/or solenoid valves, among other devices. One or more of the devices  1024  may be an intelligent electronic device. A human-machine interface  1008  may be attached to the machine controller  1020  to provide an operator with local status information about the processes under control of the machine controller  1020 , and/or local control of the machine controller  1020 . A modem  1016  may also be attached to the machine controller  1020  to provide remote access to the machine controller  1020 . 
     The PLC  1032  in this example system  1000  uses a fieldbus  1030  to communicate with actuators  1034  and sensors  1036  under its control. These actuators  1034  and sensors  1036  may include, for example, direct current (DC) servo drives, alternating current (AC) servo drives, light towers, photo eyes, and/or proximity sensors, among others. A human-machine interface  1008  may also be attached to the fieldbus  1030  to provide operators with local status and control for the PLC  1032 . A modem  1016  may also be attached to the PLC  1032  to provide remote access to the PLC  1032 . 
     The process controller  1040  in this example system  1000  also uses a fieldbus  1030  to communicate with actuators and sensors under its control, one or more of which may be intelligent electronic devices. The process controller  1040  may communicate with its fieldbus  1030  through an input/output (I/O) server  1042 . An I/O server is a control component typically responsible for collecting, buffering, and/or providing access to process information from control sub-components. An I/O server may be used for interfacing with third-party control components. Actuators and sensors under control of the process controller  1040  may include, for example, pressure regulators, pressure sensors, temperature sensors, servo valves, and/or solenoid valves, among others. The process controller  1040  may be connected to a modem  1016  so that a remote access  1050  site may access the process controller  1040 . The remote access  1050  site may include a computer  1052  for use by an operator to monitor and control the process controller  1040 . The computer  1052  may be connected to a local modem  1016  for dialing in to the modem  1016  connected to the process controller  1040 . 
     The illustrated example system  1000  also includes a single loop controller  1044 . In this example, the single loop controller  1044  interfaces with actuators  1034  and sensors  1036  with point-to-point connections, instead of a fieldbus. Point-to-point connections require a dedicated connection for each actuator  1034  and each sensor  1036 . Fieldbus networks, in contrast, do not need point-to-point connections between a controller and individual field sensors and actuators. In some implementations, a fieldbus allows greater functionality beyond control, including field device diagnostics. A fieldbus can accomplish control algorithms within the fieldbus, thereby avoiding signal routing back to a PLC for every control operation. Standard industrial communication protocols are often used on control networks and fieldbus networks. 
     The single loop controller  1044  in this example is also connected to a modem  1016 , for remote access to the single loop controller. 
     In addition to the supervisory level  1002  and field level  1004  control loops, the distributed control system  1000  may also include intermediate levels of control. For example, in the case of a distributed control system controlling a discrete part manufacturing facility, there could be an intermediate level supervisor for each cell within the plant. This intermediate level supervisor could encompass a manufacturing cell containing a machine controller that processes a part, and a robot controller that handles raw stock and final products. Additionally, the distributed control system could include several of these cells that manage field-level controllers under the main distributed control system supervisory control loop. 
     In various implementations, the distributed control system may include a corporate or enterprise layer, where an enterprise network  1080  may connect to the example production facility. The enterprise network  1080  may be, for example, located at a corporate office co-located with the facility, and connected to the control network  1018  in the supervisory level  1002 . The enterprise network  1080  may provide engineers and managers with control and visibility into the facility. The enterprise network  1080  may further include Manufacturing Execution Systems (MES)  1092 , control systems for managing and monitoring work-in-process on a factory floor. An MES can track manufacturing information in real time, receiving up-to-the-minute data from robots, machine monitors and employees. The enterprise network  1080  may also include Management Information Systems (MIS)  1094 , software and hardware applications that implement, for example, decision support systems, resource and people management applications, project management, and database retrieval applications, as well as basic business functions such as order entry and accounting. The enterprise network  1080  may further include Enterprise Resource Planning (ERP) systems  1096 , business process management software that allows an organization to use a system of integrated applications to manage the business and automate many back office functions related to technology, services, and human resources. 
     The enterprise network  1080  may further be connected to a WAN  1060 . Through the WAN  1060 , the enterprise network  1080  may connect to a distributed plant  1098 , which may include control loops and supervisory functions similar to the illustrated facility, but which may be at a different geographic location. The WAN  1060  may also connect the enterprise network to the outside world  1090 , that is, to the Internet and/or various private and public networks. In some cases, the WAN  1060  may itself include the Internet, so that the enterprise network  1080  accesses the distributed plant  1098  over the Internet. 
     As described above, SCADA systems and distributed control systems use Programmable Logic Controllers (PLCs) as the control components of an overall hierarchical system. PLCs can provide local management of processes through feedback control, as described above. In a SCADA implementation, a PLC can provide the same functionality as a Remote Terminal Unit. When used in a distributed control system, PLCs can be implemented as local controllers within a supervisory scheme. PLCs can have user-programmable memory for storing instructions, where the instructions implement specific functions such as I/O control, logic, timing, counting, proportional-integral-derivative (PID) control, communication, arithmetic, and data and file processing. 
       FIG. 11  illustrates an example of a PLC  1132  implemented in a manufacturing control process. The PLC  1132  in this example monitors and controls various devices over fieldbus network  1130 . The PLC  1132  may be connected to a LAN  1118 . An engineering workstation  1112  may also be connected to the LAN  1118 , and may include a programming interface that provides access to the PLC  1132 . A data historian  1110  on the LAN  1118  may store data produced by the PLC  1132 . 
     The PLC  1132  in this example may control a number of devices attached to its fieldbus network  1130 . These devices may include actuators, such as a DC servo drive  1122 , an AC drive  1124 , a variable frequency drive  1134 , and/or a light tower  1138 . The PLC  1132  may also monitor sensors connected to the fieldbus network  1130 , such as proximity sensors  1136 , and/or a photo eye  1142 . A human-machine interface  1108  may also be connected to the fieldbus network  1130 , and may provide local monitoring and control of the PLC  1132 . 
     Most industrial control systems were developed years ago, long before public and private networks, desktop computing, or the Internet were a common part of business operations. These well-established industrial control systems were designed to meet performance, reliability, safety, and flexibility requirements. In most cases, they were physically isolated from outside networks and based on proprietary hardware, software, and communication protocols that included basic error detection and correction capabilities, but lacked secure communication capabilities. While there was concern for reliability, maintainability, and availability when addressing statistical performance and failure, the need for cyber security measures within these systems was not anticipated. At the time, security for industrial control systems mean physically securing access to the network and the consoles that controlled the systems. 
     Internet-based technologies have since become part of modern industrial control systems. Widely available, low-cost IP devices have replaced proprietary solutions, which increases the possibility of cyber security vulnerabilities and incidents. Industrial control systems have adopted Internet-based solutions to promote corporate connectivity and remote access capabilities, and are being designed and implemented using industry standard computers, operating systems (OS) and network protocols. As a result, these systems may to resemble computer networks. This integration supports new networking capabilities, but provides less isolation for industrial control systems from the outside world than predecessor systems. Networked industrial control systems may be exposed to similar threats as are seen in computer networks, and an increased likelihood that an industrial control system can be compromised. 
     Industrial control system vendors have begun to open up their proprietary protocols and publish their protocol specifications to enable third-party manufacturers to build compatible accessories. Organizations are also transitioning from proprietary systems to less expensive, standardized technologies such as Microsoft Windows and Unix-like operating systems as well as common networking protocols such as TCP/IP to reduce costs and improve performance. Another standard contributing to this evolution of open systems is Open Platform Communications (OPC), a protocol that enables interaction between control systems and PC-based application programs. The transition to using these open protocol standards provides economic and technical benefits, but also increases the susceptibility of industrial control systems to cyber incidents. These standardized protocols and technologies have commonly known vulnerabilities, which are susceptible to sophisticated and effective exploitation tools that are widely available and relatively easy to use. 
     Industrial control systems and corporate networking systems are often interconnected as a result of several changes in information management practices, operational, and business needs. The demand for remote access has encouraged many organizations to establish connections to the industrial control system that enable of industrial control systems engineers and support personnel to monitor and control the system from points outside the control network. Many organizations have also added connections between corporate networks and industrial control systems networks to allow the organization&#39;s decision makers to obtain access to critical data about the status of their operational systems and to send instructions for the manufacture or distribution of product. 
     In early implementations this might have been done with custom applications software or via an OPC server/gateway, but, in the past ten years this has been accomplished with TCP/IP networking and standardized IP applications like File Transfer Protocol (FTP) or Extensible Markup Language (XML) data exchanges. Often, these connections were implemented without a full understanding of the corresponding security risks. In addition, corporate networks are often connected to strategic partner networks and to the Internet. Control systems also make more use of WANs and the Internet to transmit data to their remote or local stations and individual devices. This integration of control system networks with public and corporate networks increases the accessibility of control system vulnerabilities. These vulnerabilities can expose all levels of the industrial control system network architecture to complexity-induced error, adversaries and a variety of cyber threats, including worms and other malware. 
     Many industrial control system vendors have delivered systems with dial-up modems that provide remote access to ease the burdens of maintenance for the technical field support personnel. Remote access can be accomplished, for example, using a telephone number, and sometimes an access control credential (e.g., valid ID, and/or a password). Remote access may provide support staff with administrative-level access to a system. Adversaries with war dialers—simple personal computer programs that dial consecutive phone numbers looking for modems—and password cracking software could gain access to systems through these remote access capabilities. Passwords used for remote access are often common to all implementations of a particular vendor&#39;s systems and may have not been changed by the end user. These types of connections can leave a system highly vulnerable because people entering systems through vendor-installed modems are may be granted high levels of system access. 
     Organizations often inadvertently leave access links such as dial-up modems open for remote diagnostics, maintenance, and monitoring. Also, control systems increasingly utilize wireless communications systems, which can be vulnerable. Access links not protected with authentication and/or encryption have the increased risk of adversaries using these unsecured connections to access remotely controlled systems. This could lead to an adversary compromising the integrity of the data in transit as well as the availability of the system, both of which can result in an impact to public and plant safety. Data encryption may be a solution, but may not be the appropriate solution in all cases. 
     Many of the interconnections between corporate networks and industrial control systems require the integration of systems with different communications standards. The result is often an infrastructure that is engineered to move data successfully between two unique systems. Because of the complexity of integrating disparate systems, control engineers often fail to address the added burden of accounting for security risks. Control engineers may have little training in security and often network security personnel are not involved in security design. As a result, access controls designed to protect control systems from unauthorized access through corporate networks may be minimal. Protocols, such as TCP/IP and others have characteristics that often go unchecked, and this may counter any security that can be done at the network or the application levels. 
     Public information regarding industrial control system design, maintenance, interconnection, and communication may be readily available over the Internet to support competition in product choices as well as to enable the use of open standards. Industrial control system vendors also sell toolkits to help develop software that implements the various standards used in industrial control system environments. There are also many former employees, vendors, contractors, and other end users of the same industrial control system equipment worldwide who have inside knowledge about the operation of control systems and processes. 
     Information and resources are available to potential adversaries and intruders of all calibers around the world. With the available information, it is quite possible for an individual with very little knowledge of control systems to gain unauthorized access to a control system with the use of automated attack and data mining tools and a factory-set default password. Many times, these default passwords are never changed. 
     IV. Cyber Vaccines and Antibodies 
     In various implementations, the systems and methods discussed above can be used to implement cyber vaccines and antibodies. 
     Malware programs often avoid re-infecting a system twice, and so use various markers, such as files, processes, registry entries, and other data to identify systems the malware program has already infected. In various implementations, a cyber-vaccine technique includes determining a marker generated by the malware program, and using the marker to prevent other network devices from becoming infected by the same malware program. 
     Malware programs can sometimes alternatively or additionally establish “command and control” communication channels with entities outside of a site network. Using a command and control channel the malware can receive instructions and/or send valuable data to the outside entity. Cyber-antibody techniques can be used to identify network traffic sent using this communication channel. Once identified, this seemingly harmless network traffic can be deliberately “tainted” or made to carry a known malware signature so that the network traffic is blocked by a site network&#39;s security perimeter. The taint can be put on any network device, which can protect the network device from also establishing communications with the outside entity. 
     Malware programs can sometimes also detect whether the malware program is executing within a sandbox testing environment. For example, a malware program may look for the presence of particular processes or files. A generic cyber-vaccine can replicate the characteristics of a testing environment on production systems, such that productions systems—which would not be used for analyzing malware—resemble a testing environment. Malware programs designed not to trigger in a testing environment may thus not trigger on computing systems that have the generic cyber-vaccine. In this way, these computing systems can be protected from infection by malware programs that are capable of detecting their environment. 
       FIGS. 12A-12C  illustrate an example of a network  1200 , in which cyber vaccination techniques can be implemented. The example network  1200  includes a number of nodes  1210   a - 1210   f,    1280 , connected to a number of network infrastructure devices  1214   a,    1214   b.  The example network  1200  further includes a network security infrastructure  1230 , and a gateway device  1220 , through which the network  1200  can connect to other networks, including the Internet  1250 . 
     The network nodes  1210   a - 1210   f,    1280  can include a variety of devices. For example, the network nodes  1210   a - 1210   f,    1280  can include computing systems, such as server computers, laptop computers, desktop computers, smart phones, personal digital assistants, tablet computers, and so on. As another example, the network nodes  1210   a - 1210   f,    1280  can include peripheral devices, such as printers and monitors, among others. As another example, the network nodes  1210   a - 1210   f,    1280  can include storage arrays and compute farms, among other things. As another example, the network nodes  1210   a - 1210   f,    1280  can include other systems that can be connected to a network, such as entertainment systems, televisions, home appliances, factory machinery, and so on. 
     The network infrastructure devices  1214   a,    1214   b  include devices that provide network connectivity. For example, the network infrastructure devices  1214   a,    1214   b  can include routers, switches, hubs, repeaters, access points, and network monitors, among other things. The gateway device  1220  is another example of a network infrastructure device. Examples of gateway devices include modems, access points, and devices that combine modem functionality with routing or switching functionality. 
     The network security infrastructure  1230  includes hardware and software that defends the network  1200  from internal and/or external threats. For example, the network security infrastructure  1230  can include anti-virus tools, email filtering tools, firewalls, security information and event management (SIEM) tools, intrusion detection systems (IDSs), intrusion prevention systems (IPSs), and so on. In some implementations, the gateway device  1220  can alternatively or additionally include a firewall, or similar security tool. In many cases, the nodes  1210   a - 1210   f,    1280  in the network  1200  also includes network security tools, such as virus scanners and email filters. Frequently, however, a network also includes network security measures at the “perimeter” of the network; that is, where the network connects to other networks, particularly public networks such as the Internet  1250 . 
     In the example illustrated by  FIG. 12A , a node  1280  has become infected with a malware program  1290 . In various implementations, the node  1280  can include network security tools that can detect that the node  1280  has become infected. For example, scans by anti-virus tools and/or host intrusion detection systems can detect the presence of a virus or worm or similar malware. As another example, real-time system monitors may detect abnormal activity, such as parts of the file system becoming inaccessible due to ransomware encrypting files or other malware corrupting files. As another example, system monitors can detect unusually high activity, such as excessive processor or memory usage by an unknown or untrusted process. As another example, automated tools can examine event logs generated by the node&#39;s  1280  operating system and any applications running on the node  1280 . 
     Once the node  1280  has determined that it has become infected with the malware program  1290 , in various implementations the node  1280  can execute processes to identify a marker generated by the malware program  1290 . Some malware avoids infecting the same computing system more than once. For example, ransomware can operate by encrypting the data on a computing system, which the distributor of the ransomware will unencrypt upon being paid a ransom. Should the computing system be infected twice—such that the already encrypted data is encrypted again—the computing system&#39;s data may be unrecoverable, rendering the ransom request moot. 
     Malware such as ransomware may thus leave a marker on a computing system, which the malware can use to identify a system that the malware has already infected. The marker can take various forms. For example, a marker can be an entry placed in a system registry (e.g., a Windows® registry) or a similar database, one or more files or directories placed in the file system, a process running at the application or kernel level, a user account activated on the system, data placed in system memory, and/or an open network port that was not previously open. In some cases, the marker is static, while in other cases the marker temporary; for example, the marker may expire and disappear naturally (e.g., a process that terminates), the marker may be self-deleting, the marker may be deleted by the malware program, the marker may be deleted by normal operation of the operating system, and so on. 
       FIG. 12B  illustrates an example of a technique for locating and identifying a marker  1260  placed on the node  1280  by the malware program  1290 . In various implementations, the node  1280  may be configured to periodically produce snapshots  1286 . A snapshot can capture the current state of the node  1280 , including for example processing executing at the time the snapshot was taken, the contents of system memory at the time the snapshot was taken, the contents and structure of the file system, a configuration of the hardware, the contents of a system registry, the status of any user accounts currently active on the system, and so on. The node  1280  may be configured to periodically produce snapshots as backups of the node  1280 , for performance analysis, and/or for security analysis. 
     In the illustrated example, a process executing on the node  1280  can use snapshots  1286  of the system to locate and identify the malware program&#39;s  1290  marker  1260 . For example, the process can identify a “before” snapshot  1282 , that is, a snapshot taken before the malware program  1290  infected the node  1280 . The process can further identify an “after” snapshot  1284 , that is, a snapshot taken after the malware infection started. In various implementations, the after snapshot  1284  can be taken when a particular event occurs, such as the when the malware program  1290  completes a task (e.g., encrypting an entire file system, sending data to the Internet, copying itself to another system, etc.). In these implementations, Intermediate changes made by the malware program  1290  can be excluded from consideration as the marker. 
     Once the after snapshot  1284  has been obtained, the process can further compare the before snapshot  1282  to the after snapshot  1284 , and identify differences. Many of the differences can be legitimate and can be ignored. For example, processes initiated by trusted operations, files generated by legitimate uses, and/or other creation or removal of data that occurs during ordinary operation of the node  1280  can be ignored. By process of elimination, the marker  1260  can be located and identified. 
     Alternatively or additionally, the marker  1260  can be located by looking for unexpected or unknown data, data that cannot be verified, and/or data that cannot be associated with a valid or trusted process. For example, the process executing on the node  1280  can look for unknown or unidentifiable processes, files or directories with unusual names, user accounts for nonexistent users, changes to memory or files that should not occur, and so on. In some implementations, a set of differences between the before snapshot  1282  and the after snapshot  1284  can be identified, without determining precisely which of the differences are the marker  1260 . In these implementations, at least one of these differences is assumed to be the marker  1260 , and the entire set of differences may be distributed as the marker  1260 . 
     In various implementations, the marker  1260  can be a set of changes observed in the after snapshot  1284 . In these implementations, all additions and/or modifications to the file system, file system registry, new processes launched, and/or newly created mutex (a program object that allows multiple program threads to share a same resource) can, together, be considered the marker  1260 . By including all the additions and/or modifications, the system need not identify precisely which addition or modification is being used as the marker. In various implementations, the set of changes can be reduced by removing common operations, such as may be routinely conducted by the operating system, and/or operations known to be safe. In various implementations, some changes may not be included in the set, to avoid changes to other nodes  1210   a - 1210   f  that may be undesirable. For example, software uninstalls, termination of processes, loading of certain dynamic link libraries (DLL) may be excluded from the set. 
     Identification of the marker  1260  generally occurs in real time. “Real time,” in this context, means that analysis of the snapshots  1286  can occur in milliseconds, so that the result of the analysis (e.g., location and identification of the marker) is available virtually immediately. The marker  1260  can thus be determined very quickly after infection by the malware program  1290  is detected. As discussed further below, the marker  1260  further be used to quickly vaccinate other network nodes  1210   a - 1210   f  against the malware program  1290 . 
     In various implementations, analysis of the malware program  1290  can terminate once the marker  1260  has been identified. In some cases, other network security tools may analyze the malware program  1290 , including for example to reverse engineer the malware, generate a digital signature, determine the behavior of the malware, or to otherwise conduct a deep analysis of the operation of the malware. While such analysis can be useful for preventing future attacks, for purposes of the cyber vaccination technique illustrated in  FIGS. 12A-12C , this analysis is not necessary, and can be bypassed. 
     Instead, the identified marker  1260  can be used to “vaccinate” the nodes  1210   a - 1210   f  in the network. In medical terms, a vaccine can confer immunity from a particular disease.  FIG. 12C  illustrates an example where the marker  1260  generated by the malware program  1290  has been distributed to each of the un-infected nodes  1210   a - 1210   f  in the network  1200 . Specifically, a process executing on the node  1280  can, as soon as the marker  1260  is identified, distribute a copy of the marker  1260  to each of the un-infected nodes  1210   a - 1210   f.  In various implementations, distributing the marker  1260  can be accomplished using remote administration tools, such as Windows Management Interface, PowerShell, PsTools, and Active Directory Group Policy Objects, among others. Alternatively or additionally, the marker  1260  can be distributed using enterprise endpoint detection and response agents. 
     In some implementations, the process can identify any nodes  1210   a - 1210   f  in the network  1200  that are to receive the marker  1260 . For example, the process can be configured to distribute the marker  1260  specifically to nodes that have not yet been infected. As another example, a set of nodes may be designated for receiving the marker  1260 , while other nodes are not to receive the marker  1260 . In this example, these other nodes may be particularly secure, particularly sensitive, not configured to accept the marker  1260 , not have the same hardware and/or software configuration as the infected node  1280 , may not be susceptible to this particular malware program  1290 , or for some other reason will not make use of the marker  1260 . Alternatively, in some implementations, the process may be configured to automatically distribute the marker  1260  to all nodes  1210   a - 1210   f  in the network  1200 . In these implementations, each node  1210   a - 1210   f  may individually determine what to do with the marker  1260 . 
     In various implementations, when a node  1210   a - 1210   f  receives a copy of the marker  1260 , the node  1210   a - 1210   f  can place the marker  1260  in the same or similar location as where the marker  1260  was found on the infected node  1280 . For example, the node  1210   a - 1210   f  can place a similar entry in a system registry, place a file in a similar directory, launch a similar process, and/or create a similar user account. In cases where the marker  1260  is not static the node  1210   a - 1210   f  can periodically refresh the marker  1260  (e.g., by restarting the process, recreating a file or user account, etc.). 
     With the marker  1260  in place on the un-infected nodes  1210   a - 1210   f,  the nodes  1210   a - 1210   f  may be immunized from the malware program  1290 . For example, should the malware program  1290  migrate from the infected node  1280  to another node  1210   f,  the malware program  1290  may find that the second node  1210   f  already has the marker  1260 . The malware program  1290  may thus incorrectly determine that the second node  1210   f  was already infected by the malware program  1290 . Based on this determination, the malware program  1290  may not activate. Thus, even though the malware program  1290  managed to spread, the effect of the malware program  1290  may have been prevented. In some cases, when the malware program  1290  does not activate, the malware program  1290  potentially also does not spread further. In these cases, the presence of the marker  1260  on the second node  1210   f  had the additional benefit of containing the spread of the malware program  1290 . 
     Distribution of the marker  1260  can also occur in real time. For example, automated processes at the node  1280  can activate, once the marker  1260  has been identified, to send copies of the marker  1260  to other nodes  1210   a - 1210   f  in the network  1200 . In some implementations, these automated processes can remotely configure the other nodes  1210   a - 1210   f  to place a copy of the marker  1260  on the nodes  1210   a - 1210   f.  In some implementations, these automated processes can provide a copy of the marker  1260  to each node  1210   a - 1210   f,  and the nodes  1210   a - 1210   f  can include processes for placing a copy of the marker  1260  in the appropriate location. Alternatively, a node  1210   a - 1210   f  can be configured to ignore the marker  1260 . 
     Because the determination and distribution of the marker  1260  can occur in real time, generally, once the node  1280  determines that it has become infected with the malware program  1290 , the entire network  1200  can be immunized against the malware program  1290  very quickly, potentially faster than the malware program  1290  is able to spread itself. Furthermore, lengthy analysis of the functionality of the malware program  1290  is not needed and can be left for later. The cyber-vaccination technique, as discussed above, can thus provide protection against malware infections, including zero-day malware. 
       FIG. 13  illustrates another example of a network  1300  in which cyber vaccination techniques can be implemented. The example network  1300  includes a number of nodes  1310   a - 1310   f,    1380 , connected to a number of network infrastructure devices  1314   a,    1314   b.  The nodes  1310   a - 1310   f  can be one of a variety of network devices, such as computing systems, storage arrays, peripheral devices, and so on. The nodes  1310   a - 1310   f  can also be a variety of devices capable of being connected to a network, such as televisions, home appliances, manufacturing equipment, and so on. The network infrastructure devices  1314   a,    1314   b  can include a variety of devices that provide network connectivity, such as routers, switches, hubs, repeaters, access points, and so on. The example network  1300  further includes a network security infrastructure  1330 , which can include various network security tools for defending the network  1300  from threats. The example network also includes a gateway  1320 , through which the network  1300  can communicate with other networks, including the Internet  1350 . 
     In the illustrated example, the network  1300  also includes a high-interaction network  1316 . The high-interaction network  1316  is a self-contained, carefully monitored environment. The high-interaction network  1316  can include physical and virtual computing systems, which can be rapidly reconfigured to emulate all or part of the network  1300 , or some other network. In the illustrated example, the high-interaction network  1316  has been configured to include an array of compute servers  1370 , an array of file servers  1368 , and a number of user workstations  1376 ,  1378 . The example high-interaction network  1316  further includes a switch  1374  and a router  1366  that connect the various servers  1368 ,  1370  and workstations  1376 ,  1378  together. The high-interaction network  1316  further includes a firewall  1364 , which can serve to make the high-interaction network  1316  appear more like a real network. The high-interaction network  1316  further includes a gateway  1362 , through which the network emulated within the high-interaction network  1316  can communicate with other networks, including the Internet  1350 . 
     In the example of  FIG. 13 , the node  1380  has become infected with a malware program  1390 . In various implementations, the node  1380  can include processes that can identify unusual or malicious behavior on the node  1380 , which can indicate the infection by the malware program  1390 . For example, the node  1380  can include anti-virus or similar tools. In various implementations, once it has been determined that the node  1380  has become infected by the malware program  1390 , processes running on the node  1380  can send the malware program  1390  to the high-interaction network  1316  for analysis. Alternatively or additionally, in some implementations, processes executing on the node  1380  and/or in the network security infrastructure  1330 , and/or in the network&#39;s  1300  infrastructure can isolate the node  1380 . In these implementations, any further communication between the node  1380  and the rest of the network  1300  or the Internet  1350  can be redirected to the high-interaction network  1316  for analysis. 
     In some implementations, the malware program  1390 , or data associated with the malware program  1390 , may be identified by the network security infrastructure  1330 . For example, the network security infrastructure  1330  may identify questionable network traffic originating from outside or inside the network  1300 . In some cases, the questionable network traffic includes known malware. In some cases, the network traffic exhibits behavior and/or data patterns often associated with malware infiltrations or attempted infiltrations. In each of these cases, the network security infrastructure  1330  can be configured to redirect the questionable network traffic to the high-interaction network  1316 . 
     As noted above, the high-interaction network  1316  is isolated from the network  1300 . Thus, suspect network traffic, which may include the malware program  1390 , can be sent into the high-interaction network  1316 , and be activated. For example, in the illustrated example, the malware program  1390  has been activated on a user workstation  1378 . Because the high-interaction network  1316  is configured to emulate a physical network, the malware program  1390  can function as designed, and do whatever what is intended. 
     As also noted above, the high-interaction network  1316  can closely monitor the behavior of the malware program  1390 . For purposes of vaccinating the network  1300 , however, the high-interaction network  1316  can be configured to quickly identify changes made to the user workstation  1378  by the malware program  1390 , and locate a marker  1360  generated by the malware program  1390 . For example, the high-interaction network  1316  can take a snapshot of the user workstation  1378  before the malware program  1390  is activated and take a snapshot after the malware program  1390  is activated. By comparing these snapshots, the high-interaction network  1316  can identify changes made to the user workstation  1378  by the malware program  1390 . Changes such as file overwrites (such as, for example, overwrites caused by ransomware encrypting files), registry overwrites, and other changes related to the harm intended by the malware program  1390  can be ignored. Similarly, in some implementations, deletion of registry entries, changes to sensitive registry entries (such as those related to security, backup, restore, and/or anti-virus software), file system deletion or updates of application software such as anti-virus software, changes to operating system directory, loading of certain DLLs, changes to some environment variables, and/or new task schedulers may also be excluded. 
     Once the marker  1360  used by the malware program  1390  has been identified, the high-interaction network  1316  can cause the marker  1360  to be distributed to the nodes  1310   a - 1310   f  in the network  1300 . The high-interaction network  1316  can be configured with a list of particular nodes  1310   a - 1310   f  that should receive the marker  1360 , or the high-interaction network  1316  can be configured to send the marker  1360  to all the nodes  1310   a - 1310   f  in the network  1300 . The high-interaction network  1316  can, for example, use remote administration tools to send copies of the marker  1360  to the nodes  1310 - 1310   f  in the network  1300 . In some implementations, the high-interaction network  1316  can place a copy of the marker  1360  in the appropriate location on a node  1310   a - 1310   f.  In some implementations, the high-interaction network  1316  can provide a copy of the marker  1360  to a node  1310   a - 1310   f,  and the node  1310 - 1310   f  can itself determine what to do with the marker  1360 . 
     Once the marker  1360  has been distributed across the network  1300 , should the malware program  1390  spread to another node  1310   f,  or infiltrate the network  1300  again, each of the nodes  1310   a - 1310   f  that have a copy of the marker  1360  may be immunized form the malware program  1390 . For example, should the malware program  1390  migrate to a particular node  1310   f,  the malware program  1390  may find the marker  1360 , and determine not to activate. 
     Generally, identification and distribution of the marker  1360  occurs automatically and in real-time. For example, the high-interaction network  1316  can be configured to automatically trigger the malware program  1390 . The high-interaction network  1316  can further automatically execute steps that can identify the marker  1360 , and automatically distribute the marker  1360  once the marker  1360  has been identified. Because each of these processes is automated, vaccination of the network  1300  against the malware program  1390  can occur rapidly after the malware program  1390  has been triggered. 
     In various implementations, the high-interaction network  1316  need only to conduct sufficient analysis to identify the marker  1360 . In some cases, the high-interaction network  1316  can conduct further analysis into the malware program  1390 . In these cases, the high-interaction network  1316  can generate a digital signature for the malware program  1390 , and/or various indicators that can be used to identify the malware program  1390 . 
       FIGS. 14A-14C  illustrate an example of a network  1400 , in which cyber antibody techniques can be implemented. The example network  1400  includes a number of nodes  1410   a - 1410   f,    1480 , connected to a number of network infrastructure devices  1414   a,    1414   b.  The nodes  1410   a - 1410   f  can be one of a variety of network devices, such as computing systems, storage arrays, peripheral devices, and so on. The nodes  1410   a - 1410   f  can also be a variety of devices capable of being connected to a network, such as televisions, home appliances, manufacturing equipment, and so on. the network infrastructure devices  1414   a,    1414   b  can include a variety of devices that provide network connectivity, such as routers, switches, hubs, repeaters, access points, and so on. The example network  1400  further includes a network security infrastructure  1430 , which can include various network security tools for defending the network  1400  from threats. The example network also includes a gateway  1420 , through which the network  1400  can communicate with other networks, including the Internet  1450 . 
     In the example of  FIG. 14A , a node  1480  has become infected with a malware program  1490 . In various implementations, the node  1480  can include network security tools that can detect that the node  1480  has become infected. For example, routine scans by anti-virus tools can detect the presence of a virus or worm or similar malware. As another example, real-time system monitors may detect abnormal activity, such as parts of the file system becoming inaccessible due to ransomware encrypting files or other malware corrupting files. As another example, system monitors can detect unusually high activity, such as excessive processor or memory usage by an unknown or untrusted process. 
     Once the node  1480  has determined that it has become infected with the malware program  1490 , in various implementations the node  1480  can execute processes to identify network packets  1492  sent by the malware program  1490 . Some malware programs establish a communication channel with the computer systems of an outside entity, which will be referred to herein as a malicious actor  1440 . The malicious actor  1440  may be located somewhere on the Internet  1450 . In some cases, the malicious actor  1440  may be within the network  1400 . For example, the malicious actor  1440  may be using a compromised node in the network  1400 . The malware program  1490  may use the communication channel, for example, to receive instructions or commands from the malicious actor  1440 , or other data such as security keys or malicious programs. As another example, the malware program  1490  may be sending status updates to the malicious actor  1440 ; for example, a ransomware program may communicate a percentage of the node&#39;s  1480  file system that has been encrypted. As another example, the malware program  1490  may be providing information to the malicious actor  1440 , such as authentication information that opens a backdoor. As another example, the malware program  1490  may be stealing data (e.g., passwords, credit card numbers, etc.) from the network  1400 , and sending this data to the malicious actor  1440 . 
     In some cases, blocking the malware program&#39;s  1490  communication channel can be accomplished by identifying the destination address or target domain to which the malware program  1490  is sending packets  1492 . In some cases, however, the packets  1492  from the malware program  1490  may addressed to legitimate domains or addresses. For example, the packets  1492  may take the form of posts to social media sites, such as Facebook® or Twitter®. As another example, the packets  1492  may include posts to public forums such as Quora® or Yahoo Answers. In these cases, the malicious actor  1440  can obtain the information contained in the packets  1492  by monitoring these sites in a legitimate fashion, using valid accounts. In these examples, blocking all network traffic from the network  1400  to these sites can block legitimate traffic, in addition to the packets  1492  sent by the malware program  1490 . 
     In other cases, the malware program  1490  may communicate with the malicious actor  1440  through convoluted paths. For example, the malicious actor  1440  may be using proxies, “onion” routers, multi-stage exfiltration, and so on. As another example, the malware program  1490  may be communicating with a changing list of destinations, each of which may disappear as soon as the packets  1492  are received. In these cases, blocking network traffic from the network  1400  to any one destination may not be sufficient. 
     In various implementations, a cyber antibody technique can be used to block the packets  1492  from the malware program  1490  without needing to block particular destination addresses or whole domains. A cyber antibody technique includes identifying packets sent by the malware program  1490 , and then “tainting” or modifying these packets  1492  so that the packets  1492  are blocked by the network security infrastructure  1430 . 
       FIG. 14B  illustrates an example of the first stage of the cyber antibody technique. In the illustrated example, processes running on the node  1480  can monitor the packet stream  1482  originating from the node  1480 . The processes can further identify the packets  1492  associated with the malware program  1490 . Specifically, each process on the node  1480  that generates packets can be monitored, and packets from any known, trusted, or verifiable process can be ignored. In some implementations, Hypertext Transfer Protocol (HTTP) requests to retrieve data (e.g., GET requests) may also be ignored. Packets from any unknown, untrusted, or unverifiable processes, or any process that can be identified as possibly associated with the malware program  1490  can be identified as suspect packets. For example, HTTP requests to send data to a website (e.g., POST requests) can be suspect. For example, HTTP POST request can be used to exfiltrate data out of the network  1400 . As another example, Domain Name Server (DNS) requests can be used to create illicit DNS tunnels by attaching special characteristics to DNS requests. In some implementations, all of the suspect packets are assumed to be packets that should be blocked. In some implementations, the suspect packets can be further filtered to identify the specific packets that are originating from the malware program  1490 . 
     Once the packets  1492  to be blocked have been identified, processes running on the node  1480  can further determine identifying characteristics for the packets  1492 . Characteristics of the packets  1492  can include, for example, a process that generated the packets  1492 . As another example, characteristics can include fields in a header portion of the packets, such as for example a source address, a destination address, a network protocol type, an identification, and/or a label. As another example, characteristics can include data found in a payload portion of the packets  1492 , such as hashtags, random character strings, formatted character strings, text formatted using foreign character encodings, and so on. In some cases, text such as hashtags and/or formatted character strings are used by the malicious actor  1440  to locate the packets  1492  once the packets  1492  are on the Internet  1450 . 
     The node  1480  can thereafter use the characteristics to identify further packets  1492  from the malware program  1490 . These identified packets  1492  can then be “tainted.” As illustrated in  FIG. 14C , the node  1480  can include a tool, process, or filter  1434  through which packets from the node  1480  pass before being placed on the network  1400 . The filter  1434  can identify packets  1492  from the malware program  1490 , and “taint” these packets  1492  by inserted data associated with a known malware program  1494  into the packets  1492 . The data can be, for example, an executable file, an image, a document, or some other data that has previously been identified as containing malware or being generated by malware. For example HTTP POST requests can be modified to include strings known to be used to exfiltrate data. As another example, DNS packets, including DNS text messages, Extensions mechanisms for DNS (EDNS) messages, and long DNS requests, can be modified with characteristics known to be used for DNS tunneling. 
     By inserting data associated with the known malware program  1494  into the packets  1492 , the packets  1492  will be blocked by network traffic scanning tools  1432  that are part of the network security infrastructure  1430 . Network traffic scanning tools  1432 , such as firewalls, intrusion detection systems, intrusion protection systems, data loss prevention (DLP) systems, egress filtering, and others can scan outbound network traffic and block any network traffic that should not be leaving the network  1400 . Such traffic can include any packets that contain identifiable malware. By tainting outbound network traffic with characteristics of known malware, the network security infrastructure&#39;s  1430  existing rules and filters can be used to block such traffic. New rules for the unknown malware program  1490  need not be generated. 
     The network traffic scanning tools  1432  can thus block packets  1492  that have been generated by the malware program  1490  when the packets  1492  have been modified to include data associated with a known malware program  1494 . Modifying the packets  1492  can cause packets that would otherwise appear legitimate, such as posts to social media sites or forums, to appear infected. The packets  1492  are selectively modified, however, so that packets  1412  generated for legitimate purposes (e.g., by users posting to social media sites or forums) are not blocked, and can pass through the network security infrastructure  1430 . 
     In various implementations, processes executing on the node  1480  can also distribute the characteristics that identify the packets  1492  from the malware program  1490  to other nodes  1410   a - 1410   f  in the network  1400 . For example, the process can, using remote administration tools, copy the characteristics to the other nodes  1410   a - 1410   f.    
     The other nodes  1410   a - 1401   f  can also include a tool, process, or filter  1434  that can use the characteristics to identify and taint packets  1492  generated by the malware program  1490 , so that these packets  1492  will be blocked by the network security infrastructure  1430 . In some implementations, the processes on the node  1480  can configure the filters  1434  at the other nodes  1410   a - 1410   f  using, for example, remote administration tools. In some implementations, the processes on the node  1480  can make the characteristics of the packets  1492  available to the other nodes  1410   a - 1410   f,  and the nodes  1410   a - 1410   f  can configure their respective filters  1434 , or choose not to use the characteristics. 
     Alternatively or additionally, the process can infect the other nodes  1410   a - 1410   f  with the malware program  1490 , so that the other nodes  1410   a - 1410   f  can generate packets that have the same characteristics. For example, the process can copy the malware program  1490  to the other nodes  1410   a - 1410   f  and cause the malware program  1490  to be launched. Alternatively or additionally, the process can enable paths to the other nodes  1410   a - 1410   f  that are often used by malware programs to distribute themselves. For example, some malware spreads using the file system paths that lead to other devices. Thus, the process can create file system paths, such as Server Message Block (SMB) shared directories, soft links (e.g., “shortcuts”), hard links, etc., between the infected node  1480  and the other nodes  1410   a - 1410   f.  Alternatively or additionally, some malware spreads emailing itself to email addresses found in an address book or contacts list. Thus, the process can generate email addresses for the other nodes  1410   a - 1410   f,  so that, when email is sent to these email addresses, the email will be directed to the other nodes  1410   a - 1410   f.    
     The identification of the packets  1492  generated by the malware program  1490  and determination of identifying characteristics of these packets  1492  can occur in real time. Thus, the communication channel to the malicious actor  1440  can be blocked very quickly once the node  1480  has become infected. Additionally, distribution of the identifying characteristics can also occur in real time, so that other nodes  1410   a - 1410   f  in the network  1400  can also block similar communication channels, should the malware program  1490  spread to these other nodes  1410   a - 1410   f.  Deeper analysis of the packets  1492 , such as their intended purpose, destination, contents, method of operation, and so on is not needed, and can be left for later. Deeper analysis of the malware program  1490 , to determine, for example, the source of the malware program  1490 , its intended purpose, and the nature of the harm the malware program  1490  is capable of, can also be left for later. Immediate isolation of the infected node  1480 , while prudent, can also be left for later. The node  1480  can, however, in some implementations, issue alerts to network administrators to indicate the presence of the malware program  1490  and the need for action to be taken. 
       FIG. 15  illustrates another example of a network  1500  in which cyber antibody techniques can be implemented. The example network  1500  includes a number of nodes  1510   a - 1510   f,    1580 , connected to a number of network infrastructure devices  1514   a,    1514   b.  The nodes  1510   a - 1510   f  can be one of a variety of network devices, such as computing systems, storage arrays, peripheral devices, and so on. The nodes  1510   a - 1510   f  can also be a variety of devices capable of being connected to a network, such as televisions, home appliances, manufacturing equipment, and so on. The network infrastructure devices  1514   a,    1514   b  can include a variety of devices that provide network connectivity, such as routers, switches, hubs, repeaters, access points, and so on. The example network  1500  further includes a network security infrastructure  1530 , which can include various network security tools for defending the network  1500  from threats. The example network also includes a gateway  1520 , through which the network  1500  can communicate with other networks, including the Internet  1550 . 
     In the illustrated example, the network  1500  also includes a high-interaction network  1516 . The high-interaction network  1516  is a self-contained, carefully monitored environment, in which malware programs can be released, monitored, and studied. In the illustrated example, the high-interaction network  1516  has been configured to include an array of compute servers  1570 , an array of file servers  1568 , and a number of user workstations  1576 ,  1578 . The example high-interaction network  1516  further includes a switch  1574  and a router  1566  that connect the various servers  1568 ,  1570  and workstations  1576 ,  1578  together. The high-interaction network  1516  further includes a firewall  1564 , which can serve to make the high-interaction network  1516  appear more like a real network. The high-interaction network  1516  further includes a gateway  1562 , through which the network emulated within the high-interaction network  1516  can communicate with other networks, including the Internet  1550 . 
     In the example of  FIG. 15 , the node  1580  has become infected with a malware program  1590 . In various implementations, the node  1580  can include processes that can identify unusual or malicious behavior on the node  1580 , which can indicate the infection by the malware program  1590 . For example, the node  1580  can include anti-virus or similar tools. In various implementations, once it has been determined that the node  1580  has become infected by the malware program  1590 , processes running on the node  1580  can send the malware program  1590  to the high-interaction network  1516  for analysis. Alternatively or additionally, in some implementations, processes executing on the node  1580  and/or in the network security infrastructure  1530 , and/or in the network&#39;s  1500  infrastructure can isolate the node  1580 . In these implementations, any further communication between the node  1580  and the rest of the network  1500  or the Internet  1550  can be redirected to the high-interaction network  1516  for analysis. 
     In some implementations, the malware program  1590 , or data associated with the malware program  1590 , may be identified by the network security infrastructure  1530 . For example, the network security infrastructure  1530  may identify questionable network traffic originating from outside or inside the network  1500 . In some cases, the questionable network traffic includes known malware. In some cases, the network traffic exhibits behavior and/or data patterns often associated with malware infiltrations or attempted infiltrations. In each of these cases, the network security infrastructure  1530  can be configured redirect the questionable network traffic to the high-interaction network  1516 . 
     As noted above, the high-interaction network  1516  is isolated from the network  1500 . Thus, suspect network traffic, which may include the malware program  1590 , can be sent into the high-interaction network  1516 , and be activated. For example, in the illustrated example, the malware program  1590  has been activated on a user workstation  1578 . Because the high-interaction network  1516  is configured to emulate a physical network, the malware program  1590  can function as designed, and do whatever harm is intended. 
     As also noted above, the high-interaction network  1516  can closely monitor the behavior of the malware program  1590 , including watching for packets  1592  that are transmitted by the malware program  1590 . For example, the high-interaction network  1516  can isolate processes associated with or spawned by the malware program  1590 , and identify any packets  1592  that are generated by these processes. The high-interaction network  1516  can further determine characteristics of these packets  1592  that distinguish these packets  1592  from other packets in a packet stream  1582  leaving the high-interaction network  1516 . 
     Because the high-interaction network  1516  is isolated from the rest of the network  1500 , the packets  1592  can be allowed to reach a malicious actor  1540  located somewhere on the Internet  1550 , so that the behavior of the packets  1592  and the malware program  1590  can be further analyzed. 
     For purposes of the cyber antibody technique, however, this further analysis is not needed, and can be left for later. Once the packets  1592  have been identified, the distinguishing characteristics of these packets  1592  can be distributed to the nodes  1510   a - 1510   f  in the network  1500 . The characteristics can further be used to configure tools, processes, or filters  1534  that can use the characteristics to taint or modify packets that have similar characteristics. In some implementations, the high-interaction network  1516  can remotely configure the filters  1534  using, for example, remote administration tools. In some implementations, the high-interaction network  1516  can provide the characteristics to the nodes  1510   a - 1510   f,  which can then use the characteristics to configure the filters  1534 . 
     Distributing the characteristics can lead to the communication channel between the malware program  1590  and the malicious actor  1540  to be cut off, even if the malware program  1590  manages to spread to other nodes  1510   a - 1510   f  in the network  1500 . The operating of the malware program  1590  may thus be halted or at least contained. 
     Generally, analysis and identification of the packets  1592  from the malware program  1590  occurs automatically and in real time. For example, the high-interaction network  1516  can be configured to automatically trigger the malware program  1590 . The high-interaction network  1516  can further automatically execute the steps to identify the packets  1592 , and automatically distribute distinguishing characteristics of these packets across the network  1500 . Because each of these processes is automated, preemptive blocking of the malware program  1590  communication channel can occur rapidly after the malware program has been triggered. 
       FIG. 16  illustrates an example of a network  1600  that includes a sandbox testing environment  1680 . The example network  1600  includes a number of nodes  1610   a - 1610   g,  connected to a number of network infrastructure devices  1614   a,    1614   b.  The nodes  1610   a - 1610   g  can be one of a variety of network devices, such as computing systems, storage arrays, peripheral devices, and so on. The nodes  1610   a - 1610   g  can also be a variety of devices capable of being connected to a network, such as televisions, home appliances, manufacturing equipment, and so on. The network infrastructure devices  1614   a,    1614   b  can include a variety of devices that provide network connectivity, such as routers, switches, hubs, repeaters, access points, and so on. The example network  1600  further includes a network security infrastructure  1630 , which can include various network security tools for defending the network  1600  from threats. The example network also includes a gateway  1620 , through which the network  1600  can communicate with other networks, including the Internet  1650 . 
     The example network  1600  further includes an example of sandbox testing environment  1680 . The sandbox testing environment  1680  is a closed system in which a malware program  1690  can be tested and analyzed. A typical sandbox testing environment  1680  includes one or more servers  1682   a,    1682   b,  each executing a number of virtual machines  1684   a - 1684   d,    1686   a - 1686   d.  The virtual machines  1684   a - 1684   d,    1686   a - 1686   d  can be configured to resemble production network devices, such as the nodes  1610   a - 1610   g.  Suspect data  1692 , identified by the network security infrastructure  1630 , can be sent to the sandbox testing environment  1680  for analysis. Often, the sandbox testing environment does not include an outbound communication channel  1694 , to prevent any effects from malware that is being tested from spreading. 
     Virtual machines are often used in sandbox testing because virtual machines can be brought up, reconfigured, and/or shut down very quickly. Additionally, because virtual machines exist only in the memory of a host server, the operation of a virtual machine—particularly the operation of a malware program—can be closely monitored. Sandbox testing environments are often used for detailed analysis of malware programs. 
     Some malware programs, however, have been designed to detect that the malware program is within a sandbox testing environment. Such malware programs can avoid activating when in a sandbox testing environment, and thus thwart detection and/or analysis. Such malware programs can identify the sandbox testing environment by, for example, looking for a Media Access Control (MAC) address, which can uniquely identify a network interface. A MAC address typically includes an organizationally unique identifier, which can identify a manufacturer of the network interface. In a virtual machine, the organizationally unique identifier may identify the producer of the hypervisor, such as VMWare® or Xen®. This information can indicate to a malware program  1690  that the malware program  1690  has been released within a virtual machine. 
     The malware program  1690  can alternatively or additionally look for other indicators that identify the sandbox testing environment  1680 . For example, the malware program  1690  can look for entries in a system registry that are associated with hypervisors or the sandbox testing environment  1680 . As another example, the malware program  1690  can look for processes associated with virtual machines (e.g., processes running as part of the hypervisor) and/or with the sandbox testing environment  1680 . As another example, the malware program  1690  can look for files, directories, tools, and other data associated with a hypervisor or sandbox testing environment  1680 . As another example, the malware program  1690  can look at a current execution path, which may indicate that the malware program  1690  is in a virtual machine and/or in the sandbox testing environment  1680 . 
     In some cases, the malware program  1690  can further thwart analysis in the sandbox testing environment  1680  by activating only with certain triggers. The trigger can be a timer. For example, often sandbox testing spends only a few minutes attempting to analyze a suspicious file before moving on. In this way, the sandbox testing environment  1680  can test many suspect files, in an attempt to keep up with the rate of attacks. Thus, some malware may trigger after a lapse of more than a few minutes, or after a full day, or after some other time period. As another example, some malware triggers based on events that usually do not occur in a sandbox testing environment, such as a system reboot or user interaction. 
       FIG. 17  illustrates an example of a generic cyber vaccination technique, in which a malware program&#39;s  1790  anti-detection efforts can be used against it. The example network  1700  includes a number of nodes  1710   a - 1710   g,  connected to a number of network infrastructure devices  1714   a,    1714   b.  The nodes  1710   a - 1710   g  can be one of a variety of network devices, such as computing systems, storage arrays, peripheral devices, and so on. The nodes  1710   a - 1710   g  can also be a variety of devices capable of being connected to a network, such as televisions, home appliances, manufacturing equipment, and so on. The network infrastructure devices  1714   a,    1714   b  can include a variety of devices that provide network connectivity, such as routers, switches, hubs, repeaters, access points, and so on. The example network  1700  further includes a network security infrastructure  1730 , which can include various network security tools for defending the network  1700  from threats. The example network also includes a gateway  1720 , through which the network  1700  can communicate with other networks, including the Internet  1750 . 
     The nodes  1710   a - 1710   g,  in the example of  FIG. 17 , are production network devices. That is, the nodes  1710   a - 1710   g  are used for the normal network operations, or for whatever operations the owner of the network  1700  intends to use the network  1700 . Generally, normal network operations exclude testing and analyzing malware, given malware&#39;s ability to damage computing systems and/or spread across a network and do further harm. 
     As discussed above, a sandbox testing environment  1780  can include one or more servers  1782   a,    1782   b  that each can be executing a number of virtual machines  1784   a - 1784   d,    1786   a - 1786   d.  The virtual machines  1784   a - 1784   d,    1786   a - 1786   d  can be configured for identifying and analyzing malware programs. 
     In various implementations, the sandbox testing environment  1780  can also be used to determine characteristics that identify the operating environment of the virtual machines  1784   a - 1784   d,    1786   a - 1786   d  as associated with the sandbox testing environment  1780 . Such characteristics include, for example, processes associated with virtual machines, particular MAC addresses, particular entries in a system registry, the structure and/or contents of the file systems on the virtual machines  1784   a - 1784   d,    1786   a - 1786   d,  and/or a particular pattern of behavior of the virtual machines  1784   a - 1784   d,    1786   a - 1786   d.  In some implementations, determination of these characteristics can be conducted by another network device and/or by the network security infrastructure  1730 . 
     These characteristics that can identify an operating environment as being inside the sandbox testing environment  1780  can be used to immunize the nodes  1710   a - 1710   g  in the network  1700  from malware that is designed not to activate when in a sandbox. For example, virtual machines  1760   a - 1760   g  can be started on each of the nodes  1710   a - 1710   g,  and the normal operation of the nodes  1710   a - 1710   g  can be conducted within the virtual machines  1760   a - 1760   g.  As another example, instead of running virtual machines on each node  1710   a - 1710   g,  processes associated with virtual machines can be started on the nodes  1710   a - 1710   g.  As another example, files, directories, system registry entries, and/or other data found in the sandbox testing environment  1780  can be replicated on the nodes  1710   a - 1710   g.    
     Once the nodes  1710   a - 1710   g  have been made to resemble the sandbox testing environment  1780 , the nodes  1710   a - 1710   g  can be protected from certain kinds of malware attacks. For example, a malware program  1790  may find its way onto one of the nodes  1710   g.  The malware program, however, may erroneous determine that the node  1710   g  is in a sandbox, and thus—in an attempt to avoid detection—not activate. 
     In various implementations, the techniques discussed above, including cyber vaccination against specific malware, cyber antibody techniques that block a malware program&#39;s communication channel, and a generic cyber vaccination scheme, can be used in various combinations, to provide multiple, immediate defenses against malware attacks. Additionally, each technique can be used in combination with existing network security techniques and tools. 
     Specific details were given in the preceding description to provide a thorough understanding of various implementations of systems and components for cyber vaccines and antibodies. It will be understood by one of ordinary skill in the art, however, that the implementations described above may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments. 
     It is also noted that individual implementations may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed, but could have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function. 
     The term “computer-readable medium” includes, but is not limited to, portable or non-portable storage devices, optical storage devices, and various other mediums capable of storing, containing, or carrying instruction(s) and/or data. A computer-readable medium may include a non-transitory medium in which data can be stored and that does not include carrier waves and/or transitory electronic signals propagating wirelessly or over wired connections. Examples of a non-transitory medium may include, but are not limited to, a magnetic disk or tape, optical storage media such as compact disk (CD) or digital versatile disk (DVD), flash memory, memory or memory devices. A computer-readable medium may have stored thereon code and/or machine-executable instructions that may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, or the like. 
     The various examples discussed above may further be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks (e.g., a computer-program product) may be stored in a computer-readable or machine-readable medium. A processor(s), implemented in an integrated circuit, may perform the necessary tasks. 
     Where components are described as being “configured to” perform certain operations, such configuration can be accomplished, for example, by designing electronic circuits or other hardware to perform the operation, by programming programmable electronic circuits (e.g., microprocessors, or other suitable electronic circuits) to perform the operation, or any combination thereof. 
     The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the implementations disclosed herein may be implemented as electronic hardware, computer software, firmware, or combinations thereof. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure. 
     The techniques described herein may also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques may be implemented in any of a variety of devices such as general purposes computers, wireless communication device handsets, or integrated circuit devices having multiple uses including application in wireless communication device handsets and other devices. Any features described as modules or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, performs one or more of the methods described above. The computer-readable data storage medium may form part of a computer program product, which may include packaging materials. The computer-readable medium may comprise memory or data storage media, such as random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, magnetic or optical data storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and/or executed by a computer, such as propagated signals or waves. 
     The program code may be executed by a processor, which may include one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, an application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Such a processor may be configured to perform any of the techniques described in this disclosure. A general purpose processor may be a microprocessor; but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure, any combination of the foregoing structure, or any other structure or apparatus suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated software modules or hardware modules configured for cyber vaccines and antibodies. 
     As used below, any reference to a series of examples is to be understood as a reference to each of those examples disjunctively (e.g., “Examples 1-4” is to be understood as “Examples 1, 2, 3, or 4”). 
     Example 1 is a method, where the method comprises determining, by a network device infected by a malware program, a marker generated by the malware program. The marker indicates to the malware program that the network device has been infected by the malware program. Determining the marker includes identifying a placement of the marker on the network device. The method further includes identifying one or more other network devices that have not previously been infected by the malware program. The method further includes automatically distributing copies of the marker. When a copy of the marker is received at an identified network device from the one or more other network devices, the identified network device places the marker on the identified network device according to the identified placement. 
     Example 2 is the method of claim  1 , where determining the marker includes comparing a first snapshot of the network device with a second snapshot of the network device. The first snapshot was taken before the infection by the malware program started, and the second snapshot was taken at a pre-determined time after the infection started. The method further includes determining one or more differences between the first snapshot and the second snapshot. 
     Example 3 is the method of examples 1-2, where determining the marker includes determining a change in a system registry of the network device. 
     Example 4 is the method of examples 1-3, where determining the marker includes determining a change in a file system of the network device. 
     Example 5 is the method of examples 1-4, where determining the marker includes identifying a process running on the network device. 
     Example 6 is the method of examples 1-5, where determining the marker includes identifying a user logged in to the network device. 
     Example 7 is the method of examples 1-6, where determining the marker includes determining a change in a system memory of the network device. 
     Example 8 is the method of examples 1-7, where determining the marker includes identifying an open port of the network device. 
     Example 9 is the method of examples 1-8, where the method further comprises identifying the network device as infected by the malware program. 
     Example 10 is the method of examples 1-9, where the method further comprises activating the malware program on the network device. 
     Example 11 is the method of examples 1-10, where presence of a copy of the marker on a network device from the one or more other network devices represents the network device as infected by the malware program. 
     Example 12 is the method of examples 1-11, where determining the marker occurs in real time. 
     Example 13 is the method of examples 1-12, where automatically distributing the copies of the marker includes using a remote administration tool. 
     Example 14 is a network device, which includes one or more processors and a non-transitory computer-readable medium. The non-transitory compute readable medium includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations according to the method(s) of examples 1-13. 
     Example 15 is a computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions that, when executed by one or more processors, cause the one or more processors to perform steps according to the method(s) of examples 1-13. 
     Example 16 is a method, where the method comprises monitoring, by a network device infected with an unknown malware program, one or more packets sent by the network device onto a network. The method further includes identifying a packet that is associated with the unknown malware program. The packet is identified from among the monitored packets, and identifying the packet includes determining a characteristic of the packet. The method further includes identifying one or more other packets having a characteristic similar to the characteristic of the packet. The method further includes inserting data associated with a known malware program into the one or more other packets. The method further includes automatically distributing the characteristic of the packet. When the characteristic is received at another network device, the characteristic is used to identify additional packets having a characteristic similar to the characteristic of the packet. 
     Example 17 is the method of example 16, where identifying the packet associated with the malware program includes determining a process that generated the packet. 
     Example 18 is the method of examples 16-17, where determining the characteristic of the packet includes examining a header portion of the packet. 
     Example 19 is the method of examples 16-18, where examining the header portion includes identifying one or more of a source address, a destination address. a network service type, an identifier, a class, or a label. 
     Example 20 is the method of examples 16-19, where determining the characteristic of the packet includes examining a payload portion of the packet. 
     Example 21 is the method of examples 16-20, where examining the payload portion includes identifying for a character string. 
     Example 22 is the method of examples 16-21, where the data associated with the known malware program infects the one or more other packets with the known malware program. 
     Example 23 is the method of examples 16-22, where the known malware program is blocked by network security infrastructure devices. 
     Example 24 is the method of examples 16-23, where monitoring the packets includes monitoring for minutes, hours, days, or weeks. 
     Example 25 is the method of examples 16-24, where the method further comprises receiving a new characteristic from the network, wherein the new characteristic is associated with a new malware program. The method further comprises configuring a process with the new characteristic, wherein the process inserts the digital signature in other packets with a similar characteristic. 
     Example 26 is the method of examples 16-25, where identifying the packet occurs in real time. 
     Example 27 is the method of examples 16-26, where automatically distributing the characteristic includes using remote administration tools. 
     Example 28 is the method of examples 16-27, where automatically distributing the characteristic includes generating a file system path to the other network device. 
     Example 29 is the method of examples 16-28, where automatically distributing the characteristic includes generating an email address. In this example, email sent to the email address is sent to the other network device. 
     Example 30 is the method of examples 16-29, where the network includes a network security infrastructure device. The network security infrastructure device is configured to block packets that include the data associated with the known malware program. 
     Example 31 is a network device, which includes one or more processors and a non-transitory computer-readable medium. The non-transitory compute readable medium includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations according to the method(s) of examples 16-30. 
     Example 32 is a computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions that, when executed by one or more processors, cause the one or more processors to perform steps according to the method(s) of examples 16-30. 
     Example 33 is a method, where the method comprises determining, by a network device on a network, one or more characteristics of a testing environment. The testing environment is used to analyze malware programs. The method further includes configuring a production network device used in network operations. The production network device is configured using the one or more characteristics. Network operations exclude analyzing malware programs. Configuring the production network device with the one or more characteristics causes the production network device to resemble the testing environment. 
     Example 34 is the method of example 33, where the testing environment includes a virtual machine. 
     Example 35 is the method of examples 33-34, where the one or more characteristics include a process associated with a virtual machine. 
     Example 36 is the method of examples 33-35, where the one or more characteristics include a particular Media Access Control (MAC) address. 
     Example 37 is the method of examples 33-36, where the one or more characteristics include an entry in a system registry. 
     Example 38 is the method of examples 33-37, where the one or more characteristics include one or more of a structure or content of a file system. 
     Example 39 is the method of examples 33-38, where the one or more characteristics include an execution path of a process associated with the testing environment. 
     Example 40 is the method of examples 33-39, where the method further comprises automatically distributing the one or more characteristics to one or more other network devices. 
     Example 41 is the method of examples 33-40, where the method further comprises configuring the network device with the one or more characteristics. 
     Example 42 is the method of examples 33-41, where the method further comprises receiving a malware program. The malware program is configured to execute upon determining that the malware program is not in the testing environment.