Patent Publication Number: US-9894085-B1

Title: Systems and methods for categorizing processes as malicious

Description:
BACKGROUND 
     Viruses, Trojans, spyware, and other kinds of malware are a constant threat to any computing device that requires network connectivity. Many different types of security systems exist to combat these threats, ranging from browser plug-ins to virus scanners to firewalls and beyond. Countless new instances and permutations of malware are created every day, requiring security systems to be constantly updated. Many security systems look for malware not just on the basis of quickly-outdated signatures, but also by tracking each event initiated by unknown processes in order to determine whether those small events add up to a malicious overall picture. 
     Unfortunately, malware creators have adapted yet again by creating malware that splits up its suspicious actions among multiple different processes. A malicious process may not take any malicious actions directly but instead may spawn child processes that each generate only a portion of the events needed to accomplish a malicious task, making detection more difficult. Other malware may even use trusted processes to trigger some portion of the necessary events. By splitting up actions in this way, malicious processes may avoid being correctly categorized by traditional security systems that only examine a process&#39;s actions in the context of other actions performed by that same process. Accordingly, the instant disclosure identifies and addresses a need for additional and improved systems and methods for categorizing processes as malicious. 
     SUMMARY 
     As will be described in greater detail below, the instant disclosure describes various systems and methods for categorizing processes as malicious by comparing event data across multiple processes in order to detect malicious chains of events that are contributed to by multiple processes. 
     In one example, a computer-implemented method for categorizing processes as malicious may include (1) storing, in a security application that tracks event data for the computing device, data about an event triggered by an uncategorized process on the computing device, (2) storing, in the security application, new data about an additional event triggered by an additional process on the computing device that has not previously been determined by the security application to be connected to the uncategorized process, (3) comparing the new data about the additional event with the data about the event to determine whether the additional data shares a common variable with the data, (4) identifying, based on determining that the additional data shares the common variable with the data, a malicious chain of events that includes the event and the additional event, and (5) categorizing the uncategorized process as malicious in response to identifying the malicious chain of events. 
     In some examples, the computer-implemented method may further include categorizing the additional process as malicious in response to identifying the malicious chain of events. In one embodiment, the additional process may include a trusted process that has been previously categorized by the security application as non-malicious. In another embodiment, the uncategorized process and the additional process may be child processes of a parent process. 
     In one embodiment, comparing the new data about the additional event with the data about the event may include using a stateless language to compare the new data against a set of policy rules. In some embodiments, storing the data may include storing the data to a variable in global memory. In some examples, the computer-implemented method may further include undoing at least one of the event and the additional event. 
     In one embodiment, a system for implementing the above-described method may include (1) a storing module, stored in memory, that stores, in a security application that tracks event data for the computing device, data about an event triggered by an uncategorized process on the computing device and new data about an additional event triggered by an additional process on the computing device that has not previously been determined by the security application to be connected to the uncategorized process, (2) a comparison module, stored in memory, that compares the new data about the additional event with the data about the event to determine whether the additional data shares a common variable with the data, (3) an identification module, stored in memory, that identifies, based on determining that the additional data shares the common variable with the data, a malicious chain of events that may include the event and the additional event, (4) a categorization module, stored in memory, that categorizes the uncategorized process as malicious in response to identifying the malicious chain of events, and (5) at least one physical processor configured to execute the storing module, the comparison module, the identification module, and the categorization module. 
     In some examples, the above-described method may be encoded as computer-readable instructions on a non-transitory computer-readable medium. For example, a computer-readable medium may include one or more computer-executable instructions that, when executed by at least one processor of a computing device, may cause the computing device to (1) store, in a security application that tracks event data for the computing device, data about an event triggered by an uncategorized process on the computing device, (2) store, in the security application, new data about an additional event triggered by an additional process on the computing device that has not previously been determined by the security application to be connected to the uncategorized process, (3) compare the new data about the additional event with the data about the event to determine whether the additional data shares a common variable with the data, (4) identify, based on determining that the additional data shares the common variable with the data, a malicious chain of events that includes the event and the additional event, and (5) categorize the uncategorized process as malicious in response to identifying the malicious chain of events. 
     Features from any of the above-mentioned embodiments may be used in combination with one another in accordance with the general principles described herein. These and other embodiments, features, and advantages will be more fully understood upon reading the following detailed description in conjunction with the accompanying drawings and claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings illustrate a number of exemplary embodiments and are a part of the specification. Together with the following description, these drawings demonstrate and explain various principles of the instant disclosure. 
         FIG. 1  is a block diagram of an exemplary system for categorizing processes as malicious. 
         FIG. 2  is a block diagram of an additional exemplary system for categorizing processes as malicious. 
         FIG. 3  is a flow diagram of an exemplary method for categorizing processes as malicious. 
         FIG. 4  is a block diagram of exemplary event data. 
         FIG. 5  is a block diagram of an exemplary set of processes. 
         FIG. 6  is a block diagram of an exemplary computing system capable of implementing one or more of the embodiments described and/or illustrated herein. 
         FIG. 7  is a block diagram of an exemplary computing network capable of implementing one or more of the embodiments described and/or illustrated herein. 
     
    
    
     Throughout the drawings, identical reference characters and descriptions indicate similar, but not necessarily identical, elements. While the exemplary embodiments described herein are susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. However, the exemplary embodiments described herein are not intended to be limited to the particular forms disclosed. Rather, the instant disclosure covers all modifications, equivalents, and alternatives falling within the scope of the appended claims. 
     DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS 
     The present disclosure is generally directed to systems and methods for categorizing processes as malicious. As will be explained in greater detail below, by storing event data and then comparing event data not just to events generated by the same process but also to events generated by different processes, the systems and methods described herein may categorize processes as malicious by determining that the malicious processes contributed to a malicious chain of events. This may allow the systems and methods described herein to identify malicious processes that would otherwise be missed in cases where the malicious process does not initiate any events that would be flagged as malicious if examined in isolation. 
     The following will provide, with reference to  FIGS. 1-2 , detailed descriptions of exemplary systems for categorizing processes as malicious. Detailed descriptions of corresponding computer-implemented methods will also be provided in connection with  FIG. 3 . Detailed descriptions of exemplary event data will be provided in connection with  FIG. 4 . Additionally, detailed descriptions of exemplary processes will be provided in connection with  FIG. 5 . In addition, detailed descriptions of an exemplary computing system and network architecture capable of implementing one or more of the embodiments described herein will be provided in connection with  FIGS. 6 and 7 , respectively. 
       FIG. 1  is a block diagram of exemplary system  100  for categorizing processes as malicious. As illustrated in this figure, exemplary system  100  may include one or more modules  102  for performing one or more tasks. For example, and as will be explained in greater detail below, exemplary system  100  may include a storing module  104  that stores, in a security application that tracks event data for the computing device, data about an event triggered by an uncategorized process on the computing device. Storing module  104  may also store as well as new data about an additional event triggered by an additional process. Exemplary system  100  may additionally include a comparison module  106  that compares the new data about the additional event with the data about the event to determine whether the additional data shares a common variable with the data. Exemplary system  100  may also include an identification module  108  that identifies, based on determining that the additional data shares the common variable with the data, a malicious chain of events that may include the event and the additional event. Exemplary system  100  may additionally include a categorization module  110  that categorizes the uncategorized process as malicious in response to identifying the malicious chain of events. Although illustrated as separate elements, one or more of modules  102  in  FIG. 1  may represent portions of a single module or application. 
     In certain embodiments, one or more of modules  102  in  FIG. 1  may represent one or more software applications or programs that, when executed by a computing device, may cause the computing device to perform one or more tasks. For example, and as will be described in greater detail below, one or more of modules  102  may represent software modules stored and configured to run on one or more computing devices, such as computing device  202  in  FIG. 2 , computing system  610  in  FIG. 6 , and/or portions of exemplary network architecture  700  in  FIG. 7 . One or more of modules  102  in  FIG. 1  may also represent all or portions of one or more special-purpose computers configured to perform one or more tasks. 
     Exemplary system  100  in  FIG. 1  may be implemented in a variety of ways. For example, all or a portion of exemplary system  100  may represent portions of exemplary system  200  in  FIG. 2 . As shown in  FIG. 2 , system  200  may include a computing device  202 . In one example, computing device  202  may be programmed with one or more of modules  102 . 
     In one embodiment, one or more of modules  102  from  FIG. 1  may, when executed by at least one processor of computing device  202 , enable computing device  202  to categorize processes as malicious. For example, and as will be described in greater detail below, storing module  104  may store, in a security application that tracks event data for computing device  202 , data  216  about an event  208  triggered by a process  210  on computing device  202 . Before, afterwards, or at the same time, storing module  104  may also store, in the security application, data  218  about an event  212  triggered by a process  214  on computing device  202  that has not previously been determined by the security application to be connected to process  210 . When new event data is stored, comparison module  106  may compare data  218  about event  212  with data  216  about event  208  to determine whether data  218  shares a common variable with data  216 . Next, identification module  108  may identify, based on determining that data  218  shares the common variable with data  216 , a malicious chain of events that may include event  208  and event  212 . Finally, categorization module  110  may categorize process  210  as malicious in response to identifying the malicious chain of events. 
     Computing device  202  generally represents any type or form of computing device capable of reading computer-executable instructions. Examples of computing device  202  include, without limitation, laptops, tablets, desktops, servers, cellular phones, Personal Digital Assistants (PDAs), multimedia players, embedded systems, wearable devices (e.g., smart watches, smart glasses, etc.), gaming consoles, combinations of one or more of the same, exemplary computing system  610  in  FIG. 6 , or any other suitable computing device. 
       FIG. 3  is a flow diagram of an exemplary computer-implemented method  300  for categorizing processes as malicious. The steps shown in  FIG. 3  may be performed by any suitable computer-executable code and/or computing system. In some embodiments, the steps shown in  FIG. 3  may be performed by one or more of the components of system  100  in  FIG. 1 , system  200  in  FIG. 2 , computing system  610  in  FIG. 6 , and/or portions of exemplary network architecture  700  in  FIG. 7 . 
     As illustrated in  FIG. 3 , at step  302 , one or more of the systems described herein may store, in a security application that tracks event data for the computing device, data about an event triggered by an uncategorized process on the computing device. For example, storing module  104  may, as part of computing device  202  in  FIG. 2 , store, in a security application that tracks event data for computing device  202 , data  216  about event  208  triggered by process  210  on computing device  202 . 
     The term “security application,” as used herein, generally refers to any application that is capable of storing data about events and/or categorizing processes as malicious or non-malicious. In some embodiments, a security application may store event data for many categories of events on a computing device, compare data from different events, and/or use event data to determine whether or not a process is malicious. 
     The term “event,” as used herein, generally refers to any action or occurrence that takes place on a computing system. In some embodiments, events may be generated by applications, processes, and/or operating systems. Exemplary types of events may include file system events, registry events, and/or process events. 
     The term “uncategorized process,” as used herein, generally refers to any process that has not previously been categorized as malicious. In some embodiments, an uncategorized process may not previously have been categorized at all (e.g., may also not have been categorized as benign and/or non-malicious). 
     The term “data,” as used herein, generally refers to any variable and/or collection of variables that may describe an event. In one example, data about an event may include a name and/or identifier of a process that triggered the event, a target of the event, and/or a timestamp of the event. 
     Storing module  104  may store the data in a variety of different ways. For example, storing module  104  may store the data to a variable in global memory. In one embodiment, storing module  104  may be part of a security application that may store data from a variety of events in order to detect malicious processes. 
     At step  304 , one or more of the systems described herein may store, in the security application, new data about an additional event triggered by an additional process on the computing device that has not previously been determined by the security application to be connected to the uncategorized process. For example, storing module  104  may, as part of computing device  202  in  FIG. 2 , store, in the security application, data  218  about event  212  triggered by process  214  on computing device  202  that has not previously been determined by the security application to be connected to process  210 . 
     The term “connected,” as used herein, generally refers to any evidence-supported relationship between two processes. For example, a process that downloaded a second process may have previously been determined to be connected to the second process. In another example, if two processes were downloaded from the same source, the two processes may have previously been determined to be connected. Additionally or alternatively, if two processes share the same publisher, the processes may have been previously determined to be connected. 
     Storing module  104  may store data about the event and the additional event in any order. In some examples, the event may occur before the additional event. In other examples, the additional event may occur before the event. Additionally or alternatively, the event and the additional event may occur simultaneously. 
     At step  306 , one or more of the systems described herein may compare the new data about the additional event with the data about the event to determine whether the additional data shares a common variable with the data. For example, comparison module  106  may, as part of computing device  202  in  FIG. 2 , compare data  218  about event  212  with data  216  about event  208  to determine whether data  216  shares a common variable with data  218 . 
     The term “common variable,” as used herein, generally refers to any variable or related set of variables that are identical or similar between two sets of event data. For example, if two events target the same process, the process may be the common variable. In another example, if two events target the same file, the file may be the common variable. In some embodiments, the common variable may be a combination of several variables. For example, as illustrated in  FIG. 4 , event data  402  may be a data record that includes information about a file creation event and/or event data  404  may be a data record that includes information about a registry key creation event. In this example, event data  402  and event data  404  may share a common variable because the file name and path from event data  402  may, when combined, be identical to the path variable from event data  404 . 
     Comparison module  106  may compare the event data in a variety of ways. For example, comparison module  106  may compare the new data about the additional event with the data about the event by using a stateless language to compare the new data against a set of policy rules. In one embodiment, a stateless language may check if certain events are triggered in a pre-defined order with certain event-specific data, which are only available in the context of events. 
     In one example, one process may create an executable file while another process creates the registry run key value that points to the newly created executable file. In this example, comparison module  106  may compare variables in the global context and detect that the executable file path created by the first process is equal to the run key value created by the second process. In one embodiment, comparison module  106  may make this comparison using rules for a stateless rules engine. The first rule may be triggered on a file creation event in the context of the first process. The second rule may be triggered in the context of the second process on the registry event. Whenever either rule is matched, comparison module  106  may assign a variable to one of the corresponding items of event data and/or generate a special “rule match event” for each of the actor processes. When comparison module  106  generates this special rule match event for the second time, the third rule may be triggered, and, as a result, the signature may be triggered for both of the participating actors. In this example, comparison module  106  may then determine that the two sets of event data share a common variable. 
     Returning to  FIG. 3 , at step  308 , one or more of the systems described herein may identify, based on determining that the additional data shares the common variable with the data, a malicious chain of events that may include the event and the additional event. For example, identification module  108  may, as part of computing device  202  in  FIG. 2 , identify, based on determining that the additional data  216  shares the common variable with data  218 , a malicious chain of events that may include event  208  and event  212 . 
     The term “malicious chain of events,” as used herein, generally refers to any series of events that, in combination, perform a malicious function. For example, a file copy event may not individually be a malicious event and a file encryption event may also not individually be a malicious event. But a file copy event and a file encryption event directed to the same file may be evidence of the actions of malicious ransomware. In another example, a file creation event may not be a malicious event and a registry key creation event may also not be a malicious event, but in combination, the two events may cause a malicious chain of events that causes a potentially malicious process to execute at boot time. 
     Identification module  108  may identify a malicious chain of events in a variety of ways. For example, identification module  108  may include heuristics for identifying malicious chains of events. In another example, identification module  108  may include pre-set lists of events that, when executed in sequence, form a malicious chain of events. In some examples, identification module  108  may identify a malicious chain of events that includes more than two events that share one or more common variables. For example, identification module  108  may identify a malicious chain of events that includes four events initiated by three processes. 
     At step  310 , one or more of the systems described herein may categorize the uncategorized process as malicious in response to identifying the malicious chain of events. For example, categorization module  110  may, as part of computing device  202  in  FIG. 2 , categorize process  210  as malicious in response to identifying the malicious chain of events. 
     Categorization module  110  may take a variety of actions in conjunction with categorizing the process as malicious. For example, categorization module  110  may inform a user and/or administrator that a malicious process has been detected. In another example, categorization module  110  may delete the malicious process. In one embodiment, categorization module  110  may store information about the malicious process so that the malicious process can be recognized in the future. Additionally or alternatively, categorization module  110  may undo any or all of the events in the malicious chain of events. For example, categorization module may delete created files, remove added registry keys, and/or replace moved files. 
     In some examples, categorization module  110  may categorize the additional process as malicious in response to identifying the malicious chain of events. In some embodiments, categorization module  110  may be more likely to categorize the additional process as malicious if the additional process is a child of the same parent process as the malicious process and/or exhibits suspicious traits, such as being an unrecognized process from an unknown publisher. 
     In other examples, the additional process may include a trusted process that has been previously categorized by the security application as non-malicious. For example, an uncategorized process may launch reg.exe, a MICROSOFT-signed process, with parameters that direct reg.exe to add a registry key for a process created by the uncategorized process. The systems described herein may detect that the event initiated by reg.exe shares a common variable with the event initiated by the uncategorized process, determine that the uncategorized process is a malicious process, and exonerate reg.exe on the basis of reg.exe being a trusted process. 
     In one example, the uncategorized process and the additional process may be child processes of a parent process. For example, as illustrated in  FIG. 5 , a parent process  502  may have a child process  504  and/or a child process  506 . In this example, child process  504  may initiate file creation event  508  and/or child process  506  may initiate registry change event  510 . In this example, a malicious chain of events may occur but no one process may have initiated more than one suspicious event and parent process  502  may have directly initiated no suspicious events. In some embodiments, if categorization module  110  categorizes a process as malicious, categorization module  110  may also categorize the parent process as malicious and/or remove the parent process. 
     As explained in connection with method  300  above, the systems and methods described herein may detect malicious processes that may otherwise evade detection. The systems and methods described herein may store event data about events generated by processes in variables in global memory and may use a stateless rules engine to compare event data across processes, allowing the systems described herein to detect malicious activity that is performed by a combination of processes. After determining that a process is involved in a malicious chain of events, the systems and methods described herein may categorize the process as malicious and/or take further security actions. 
       FIG. 6  is a block diagram of an exemplary computing system  610  capable of implementing one or more of the embodiments described and/or illustrated herein. For example, all or a portion of computing system  610  may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the steps described herein (such as one or more of the steps illustrated in  FIG. 3 ). All or a portion of computing system  610  may also perform and/or be a means for performing any other steps, methods, or processes described and/or illustrated herein. 
     Computing system  610  broadly represents any single or multi-processor computing device or system capable of executing computer-readable instructions. Examples of computing system  610  include, without limitation, workstations, laptops, client-side terminals, servers, distributed computing systems, handheld devices, or any other computing system or device. In its most basic configuration, computing system  610  may include at least one processor  614  and a system memory  616 . 
     Processor  614  generally represents any type or form of physical processing unit (e.g., a hardware-implemented central processing unit) capable of processing data or interpreting and executing instructions. In certain embodiments, processor  614  may receive instructions from a software application or module. These instructions may cause processor  614  to perform the functions of one or more of the exemplary embodiments described and/or illustrated herein. 
     System memory  616  generally represents any type or form of volatile or non-volatile storage device or medium capable of storing data and/or other computer-readable instructions. Examples of system memory  616  include, without limitation, Random Access Memory (RAM), Read Only Memory (ROM), flash memory, or any other suitable memory device. Although not required, in certain embodiments computing system  610  may include both a volatile memory unit (such as, for example, system memory  616 ) and a non-volatile storage device (such as, for example, primary storage device  632 , as described in detail below). In one example, one or more of modules  102  from  FIG. 1  may be loaded into system memory  616 . 
     In certain embodiments, exemplary computing system  610  may also include one or more components or elements in addition to processor  614  and system memory  616 . For example, as illustrated in  FIG. 6 , computing system  610  may include a memory controller  618 , an Input/Output (I/O) controller  620 , and a communication interface  622 , each of which may be interconnected via a communication infrastructure  612 . Communication infrastructure  612  generally represents any type or form of infrastructure capable of facilitating communication between one or more components of a computing device. Examples of communication infrastructure  612  include, without limitation, a communication bus (such as an Industry Standard Architecture (ISA), Peripheral Component Interconnect (PCI), PCI Express (PCIe), or similar bus) and a network. 
     Memory controller  618  generally represents any type or form of device capable of handling memory or data or controlling communication between one or more components of computing system  610 . For example, in certain embodiments memory controller  618  may control communication between processor  614 , system memory  616 , and I/O controller  620  via communication infrastructure  612 . 
     I/O controller  620  generally represents any type or form of module capable of coordinating and/or controlling the input and output functions of a computing device. For example, in certain embodiments I/O controller  620  may control or facilitate transfer of data between one or more elements of computing system  610 , such as processor  614 , system memory  616 , communication interface  622 , display adapter  626 , input interface  630 , and storage interface  634 . 
     Communication interface  622  broadly represents any type or form of communication device or adapter capable of facilitating communication between exemplary computing system  610  and one or more additional devices. For example, in certain embodiments communication interface  622  may facilitate communication between computing system  610  and a private or public network including additional computing systems. Examples of communication interface  622  include, without limitation, a wired network interface (such as a network interface card), a wireless network interface (such as a wireless network interface card), a modem, and any other suitable interface. In at least one embodiment, communication interface  622  may provide a direct connection to a remote server via a direct link to a network, such as the Internet. Communication interface  622  may also indirectly provide such a connection through, for example, a local area network (such as an Ethernet network), a personal area network, a telephone or cable network, a cellular telephone connection, a satellite data connection, or any other suitable connection. 
     In certain embodiments, communication interface  622  may also represent a host adapter configured to facilitate communication between computing system  610  and one or more additional network or storage devices via an external bus or communications channel. Examples of host adapters include, without limitation, Small Computer System Interface (SCSI) host adapters, Universal Serial Bus (USB) host adapters, Institute of Electrical and Electronics Engineers (IEEE) 1394 host adapters, Advanced Technology Attachment (ATA), Parallel ATA (PATA), Serial ATA (SATA), and External SATA (eSATA) host adapters, Fibre Channel interface adapters, Ethernet adapters, or the like. Communication interface  622  may also allow computing system  610  to engage in distributed or remote computing. For example, communication interface  622  may receive instructions from a remote device or send instructions to a remote device for execution. 
     As illustrated in  FIG. 6 , computing system  610  may also include at least one display device  624  coupled to communication infrastructure  612  via a display adapter  626 . Display device  624  generally represents any type or form of device capable of visually displaying information forwarded by display adapter  626 . Similarly, display adapter  626  generally represents any type or form of device configured to forward graphics, text, and other data from communication infrastructure  612  (or from a frame buffer, as known in the art) for display on display device  624 . 
     As illustrated in  FIG. 6 , exemplary computing system  610  may also include at least one input device  628  coupled to communication infrastructure  612  via an input interface  630 . Input device  628  generally represents any type or form of input device capable of providing input, either computer or human generated, to exemplary computing system  610 . Examples of input device  628  include, without limitation, a keyboard, a pointing device, a speech recognition device, or any other input device. 
     As illustrated in  FIG. 6 , exemplary computing system  610  may also include a primary storage device  632  and a backup storage device  633  coupled to communication infrastructure  612  via a storage interface  634 . Storage devices  632  and  633  generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions. For example, storage devices  632  and  633  may be a magnetic disk drive (e.g., a so-called hard drive), a solid state drive, a floppy disk drive, a magnetic tape drive, an optical disk drive, a flash drive, or the like. Storage interface  634  generally represents any type or form of interface or device for transferring data between storage devices  632  and  633  and other components of computing system  610 . 
     In certain embodiments, storage devices  632  and  633  may be configured to read from and/or write to a removable storage unit configured to store computer software, data, or other computer-readable information. Examples of suitable removable storage units include, without limitation, a floppy disk, a magnetic tape, an optical disk, a flash memory device, or the like. Storage devices  632  and  633  may also include other similar structures or devices for allowing computer software, data, or other computer-readable instructions to be loaded into computing system  610 . For example, storage devices  632  and  633  may be configured to read and write software, data, or other computer-readable information. Storage devices  632  and  633  may also be a part of computing system  610  or may be a separate device accessed through other interface systems. 
     Many other devices or subsystems may be connected to computing system  610 . Conversely, all of the components and devices illustrated in  FIG. 6  need not be present to practice the embodiments described and/or illustrated herein. The devices and subsystems referenced above may also be interconnected in different ways from that shown in  FIG. 6 . Computing system  610  may also employ any number of software, firmware, and/or hardware configurations. For example, one or more of the exemplary embodiments disclosed herein may be encoded as a computer program (also referred to as computer software, software applications, computer-readable instructions, or computer control logic) on a computer-readable medium. The term “computer-readable medium,” as used herein, generally refers to any form of device, carrier, or medium capable of storing or carrying computer-readable instructions. Examples of computer-readable media include, without limitation, transmission-type media, such as carrier waves, and non-transitory-type media, such as magnetic-storage media (e.g., hard disk drives, tape drives, and floppy disks), optical-storage media (e.g., Compact Disks (CDs), Digital Video Disks (DVDs), and BLU-RAY disks), electronic-storage media (e.g., solid-state drives and flash media), and other distribution systems. 
     The computer-readable medium containing the computer program may be loaded into computing system  610 . All or a portion of the computer program stored on the computer-readable medium may then be stored in system memory  616  and/or various portions of storage devices  632  and  633 . When executed by processor  614 , a computer program loaded into computing system  610  may cause processor  614  to perform and/or be a means for performing the functions of one or more of the exemplary embodiments described and/or illustrated herein. Additionally or alternatively, one or more of the exemplary embodiments described and/or illustrated herein may be implemented in firmware and/or hardware. For example, computing system  610  may be configured as an Application Specific Integrated Circuit (ASIC) adapted to implement one or more of the exemplary embodiments disclosed herein. 
       FIG. 7  is a block diagram of an exemplary network architecture  700  in which client systems  710 ,  720 , and  730  and servers  740  and  745  may be coupled to a network  750 . As detailed above, all or a portion of network architecture  700  may perform and/or be a means for performing, either alone or in combination with other elements, one or more of the steps disclosed herein (such as one or more of the steps illustrated in  FIG. 3 ). All or a portion of network architecture  700  may also be used to perform and/or be a means for performing other steps and features set forth in the instant disclosure. 
     Client systems  710 ,  720 , and  730  generally represent any type or form of computing device or system, such as exemplary computing system  610  in  FIG. 6 . Similarly, servers  740  and  745  generally represent computing devices or systems, such as application servers or database servers, configured to provide various database services and/or run certain software applications. Network  750  generally represents any telecommunication or computer network including, for example, an intranet, a WAN, a LAN, a PAN, or the Internet. In one example, client systems  710 ,  720 , and/or  730  and/or servers  740  and/or  745  may include all or a portion of system  100  from  FIG. 1 . 
     As illustrated in  FIG. 7 , one or more storage devices  760 ( 1 )-(N) may be directly attached to server  740 . Similarly, one or more storage devices  770 ( 1 )-(N) may be directly attached to server  745 . Storage devices  760 ( 1 )-(N) and storage devices  770 ( 1 )-(N) generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions. In certain embodiments, storage devices  760 ( 1 )-(N) and storage devices  770 ( 1 )-(N) may represent Network-Attached Storage (NAS) devices configured to communicate with servers  740  and  745  using various protocols, such as Network File System (NFS), Server Message Block (SMB), or Common Internet File System (CIFS). 
     Servers  740  and  745  may also be connected to a Storage Area Network (SAN) fabric  780 . SAN fabric  780  generally represents any type or form of computer network or architecture capable of facilitating communication between a plurality of storage devices. SAN fabric  780  may facilitate communication between servers  740  and  745  and a plurality of storage devices  790 ( 1 )-(N) and/or an intelligent storage array  795 . SAN fabric  780  may also facilitate, via network  750  and servers  740  and  745 , communication between client systems  710 ,  720 , and  730  and storage devices  790 ( 1 )-(N) and/or intelligent storage array  795  in such a manner that devices  790 ( 1 )-(N) and array  795  appear as locally attached devices to client systems  710 ,  720 , and  730 . As with storage devices  760 ( 1 )-(N) and storage devices  770 ( 1 )-(N), storage devices  790 ( 1 )-(N) and intelligent storage array  795  generally represent any type or form of storage device or medium capable of storing data and/or other computer-readable instructions. 
     In certain embodiments, and with reference to exemplary computing system  610  of  FIG. 6 , a communication interface, such as communication interface  622  in  FIG. 6 , may be used to provide connectivity between each client system  710 ,  720 , and  730  and network  750 . Client systems  710 ,  720 , and  730  may be able to access information on server  740  or  745  using, for example, a web browser or other client software. Such software may allow client systems  710 ,  720 , and  730  to access data hosted by server  740 , server  745 , storage devices  760 ( 1 )-(N), storage devices  770 ( 1 )-(N), storage devices  790 ( 1 )-(N), or intelligent storage array  795 . Although  FIG. 7  depicts the use of a network (such as the Internet) for exchanging data, the embodiments described and/or illustrated herein are not limited to the Internet or any particular network-based environment. 
     In at least one embodiment, all or a portion of one or more of the exemplary embodiments disclosed herein may be encoded as a computer program and loaded onto and executed by server  740 , server  745 , storage devices  760 ( 1 )-(N), storage devices  770 ( 1 )-(N), storage devices  790 ( 1 )-(N), intelligent storage array  795 , or any combination thereof. All or a portion of one or more of the exemplary embodiments disclosed herein may also be encoded as a computer program, stored in server  740 , run by server  745 , and distributed to client systems  710 ,  720 , and  730  over network  750 . 
     As detailed above, computing system  610  and/or one or more components of network architecture  700  may perform and/or be a means for performing, either alone or in combination with other elements, one or more steps of an exemplary method for categorizing processes as malicious. 
     While the foregoing disclosure sets forth various embodiments using specific block diagrams, flowcharts, and examples, each block diagram component, flowchart step, operation, and/or component described and/or illustrated herein may be implemented, individually and/or collectively, using a wide range of hardware, software, or firmware (or any combination thereof) configurations. In addition, any disclosure of components contained within other components should be considered exemplary in nature since many other architectures can be implemented to achieve the same functionality. 
     In some examples, all or a portion of exemplary system  100  in  FIG. 1  may represent portions of a cloud-computing or network-based environment. Cloud-computing environments may provide various services and applications via the Internet. These cloud-based services (e.g., software as a service, platform as a service, infrastructure as a service, etc.) may be accessible through a web browser or other remote interface. Various functions described herein may be provided through a remote desktop environment or any other cloud-based computing environment. 
     In various embodiments, all or a portion of exemplary system  100  in  FIG. 1  may facilitate multi-tenancy within a cloud-based computing environment. In other words, the software modules described herein may configure a computing system (e.g., a server) to facilitate multi-tenancy for one or more of the functions described herein. For example, one or more of the software modules described herein may program a server to enable two or more clients (e.g., customers) to share an application that is running on the server. A server programmed in this manner may share an application, operating system, processing system, and/or storage system among multiple customers (i.e., tenants). One or more of the modules described herein may also partition data and/or configuration information of a multi-tenant application for each customer such that one customer cannot access data and/or configuration information of another customer. 
     According to various embodiments, all or a portion of exemplary system  100  in  FIG. 1  may be implemented within a virtual environment. For example, the modules and/or data described herein may reside and/or execute within a virtual machine. As used herein, the term “virtual machine” generally refers to any operating system environment that is abstracted from computing hardware by a virtual machine manager (e.g., a hypervisor). Additionally or alternatively, the modules and/or data described herein may reside and/or execute within a virtualization layer. As used herein, the term “virtualization layer” generally refers to any data layer and/or application layer that overlays and/or is abstracted from an operating system environment. A virtualization layer may be managed by a software virtualization solution (e.g., a file system filter) that presents the virtualization layer as though it were part of an underlying base operating system. For example, a software virtualization solution may redirect calls that are initially directed to locations within a base file system and/or registry to locations within a virtualization layer. 
     In some examples, all or a portion of exemplary system  100  in  FIG. 1  may represent portions of a mobile computing environment. Mobile computing environments may be implemented by a wide range of mobile computing devices, including mobile phones, tablet computers, e-book readers, personal digital assistants, wearable computing devices (e.g., computing devices with a head-mounted display, smartwatches, etc.), and the like. In some examples, mobile computing environments may have one or more distinct features, including, for example, reliance on battery power, presenting only one foreground application at any given time, remote management features, touchscreen features, location and movement data (e.g., provided by Global Positioning Systems, gyroscopes, accelerometers, etc.), restricted platforms that restrict modifications to system-level configurations and/or that limit the ability of third-party software to inspect the behavior of other applications, controls to restrict the installation of applications (e.g., to only originate from approved application stores), etc. Various functions described herein may be provided for a mobile computing environment and/or may interact with a mobile computing environment. 
     In addition, all or a portion of exemplary system  100  in  FIG. 1  may represent portions of, interact with, consume data produced by, and/or produce data consumed by one or more systems for information management. As used herein, the term “information management” may refer to the protection, organization, and/or storage of data. Examples of systems for information management may include, without limitation, storage systems, backup systems, archival systems, replication systems, high availability systems, data search systems, virtualization systems, and the like. 
     In some embodiments, all or a portion of exemplary system  100  in  FIG. 1  may represent portions of, produce data protected by, and/or communicate with one or more systems for information security. As used herein, the term “information security” may refer to the control of access to protected data. Examples of systems for information security may include, without limitation, systems providing managed security services, data loss prevention systems, identity authentication systems, access control systems, encryption systems, policy compliance systems, intrusion detection and prevention systems, electronic discovery systems, and the like. 
     According to some examples, all or a portion of exemplary system  100  in  FIG. 1  may represent portions of, communicate with, and/or receive protection from one or more systems for endpoint security. As used herein, the term “endpoint security” may refer to the protection of endpoint systems from unauthorized and/or illegitimate use, access, and/or control. Examples of systems for endpoint protection may include, without limitation, anti-malware systems, user authentication systems, encryption systems, privacy systems, spam-filtering services, and the like. 
     The process parameters and sequence of steps described and/or illustrated herein are given by way of example only and can be varied as desired. For example, while the steps illustrated and/or described herein may be shown or discussed in a particular order, these steps do not necessarily need to be performed in the order illustrated or discussed. The various exemplary methods described and/or illustrated herein may also omit one or more of the steps described or illustrated herein or include additional steps in addition to those disclosed. 
     While various embodiments have been described and/or illustrated herein in the context of fully functional computing systems, one or more of these exemplary embodiments may be distributed as a program product in a variety of forms, regardless of the particular type of computer-readable media used to actually carry out the distribution. The embodiments disclosed herein may also be implemented using software modules that perform certain tasks. These software modules may include script, batch, or other executable files that may be stored on a computer-readable storage medium or in a computing system. In some embodiments, these software modules may configure a computing system to perform one or more of the exemplary embodiments disclosed herein. 
     In addition, one or more of the modules described herein may transform data, physical devices, and/or representations of physical devices from one form to another. For example, one or more of the modules recited herein may receive event data to be transformed, transform the event data into a set of variables, output a result of the transformation to global storage, use the result of the transformation to compare data from different events, and store the result of the transformation to global storage. Additionally or alternatively, one or more of the modules recited herein may transform a processor, volatile memory, non-volatile memory, and/or any other portion of a physical computing device from one form to another by executing on the computing device, storing data on the computing device, and/or otherwise interacting with the computing device. 
     The preceding description has been provided to enable others skilled in the art to best utilize various aspects of the exemplary embodiments disclosed herein. This exemplary description is not intended to be exhaustive or to be limited to any precise form disclosed. Many modifications and variations are possible without departing from the spirit and scope of the instant disclosure. The embodiments disclosed herein should be considered in all respects illustrative and not restrictive. Reference should be made to the appended claims and their equivalents in determining the scope of the instant disclosure. 
     Unless otherwise noted, the terms “connected to” and “coupled to” (and their derivatives), as used in the specification and claims, are to be construed as permitting both direct and indirect (i.e., via other elements or components) connection. In addition, the terms “a” or “an,” as used in the specification and claims, are to be construed as meaning “at least one of.” Finally, for ease of use, the terms “including” and “having” (and their derivatives), as used in the specification and claims, are interchangeable with and have the same meaning as the word “comprising.”