Abstract:
Systems and methods for correlating and distributing intrusion alert information among collaborating computer systems are provided. These systems and methods provide an alert correlator and an alert distributor that enable early signs of an attack to be detected and rapidly disseminated to collaborating systems. The alert correlator utilizes data structures to correlate alert detections and provide a mechanism through which threat information can be revealed to other collaborating systems. The alert distributor uses an efficient technique to group collaborating systems and then pass data between certain members of those groups according to a schedule. In this way data can be routinely distributed, without generating excess traffic loads.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
       [0001]    This application is a continuation under 35 U.S.C. §120 of U.S. patent application Ser. No. 12/833,743, filed Jul. 9, 2010, which claims the benefit under 35 U.S.C. §120 of U.S. patent application Ser. No. 10/864,226, filed Jun. 9, 2004, which claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Patent Application No. 60/570,349, filed May 11, 2004, all of which are hereby incorporated, by reference herein in their entireties. 
     
    
     BACKGROUND 
       [0002]    The present invention relates to computer network security. More particularly, the present invention relates to systems and methods for correlating and distributing intrusion alert information among collaborating computer systems. 
         [0003]    Computer viruses, worms, trojans, hackers, malicious executables, network application errors, misuse of computer systems, scans, probes, etc. (collectively hereinafter “threats”) are constant menace to all owners, operators, and users of computers connected to public computer networks (such as the Internet) and/or private networks (such as corporate computer networks). These owners, operators, and users (collectively hereinafter “users”) include universities, businesses, governments, non-profit organizations, individuals, families, etc. (collectively hereinafter “entities”). These threats are not just an inconvenience to these owners, operators, and users, but also a major economic drain. For example, it has been reported that computer threats caused 813 billion worth of economic losses in the year 2003. 
         [0004]    Although many computers are protected by firewalls and antivirus software, these preventative measures are not always adequate. For example, a recently launched worm took advantage of a known vulnerability in a popular firewall technology the day after the public became aware of the vulnerability. Because of the rapid launch of the worm, the patch necessary to correct the vulnerability could not be deployed in time to prevent the attack. Similarly, most antivirus software relies on updates to that software so that signatures of known viruses can be utilized to recognize threats. In the case of a “zero-day” threat (e.g., a threat that has just been launched), most computer systems are completely vulnerable because no known patch or signature update has yet been made available. 
         [0005]    Like many non-computer attacks, computer attacks are usually preceded by reconnaissance activity. For example, prior to launching a worm, it may be useful for the nefarious computer user or hacker to identify computers, particular ports, and their associated services subject to a target vulnerability. Because a scan is more likely to go unnoticed, or be ignored, than an attack, the hacker is able to identify a large number of potential targets without detection. Then, when an adequate number of targets have been identified, the hacker can launch the worm against all of the identified targets simultaneously rather than attacking the targets as they are found during scanning. In this way, the hacker can cause greater damage because the distribution of the worm at first detection is likely to be widespread. When performing this reconnaissance, the hacker may scan or probe potential victims at a slow or random rate to avoid detection by the victim. In order to maximize the likelihood of quickly finding targets, the hacker may configure the scanning, and probing to scan unrelated potential victims at substantially the same time, but scan related targets only infrequently. 
         [0006]    Collaborative security systems wherein multiple systems cooperate to defend against threats may be useful in mitigating some of the exposure caused by random and infrequent scanning and probing. A problem with prior attempts at collaborative security systems, however, is that many entities are unwilling to share information regarding the identity of parties accessing their systems because of legal, public-relations, and competitive reasons. For example, a corporation may be reluctant to reveal the IP address of a suspected hacker to other corporations for fear that the suspected hacker is not in fact a hacker, but instead a valued customer. 
         [0007]    Accordingly, it is desirable to provide new systems and methods for collaboratively detecting and defending against scans, probes, viruses, and other threats in a computer network environments. 
       SUMMARY OF THE INVENTION 
       [0008]    In accordance with the present invention, systems and methods for correlating and distributing, intrusion alert information among collaborating computer systems are provided. These systems and methods provide an alert correlator and an alert distributor that enable early signs of a threat to be detected and rapidly disseminated among collaborating systems. The alert correlator stores information related to a threat, correlates alert detections, and provides a mechanism through which threat information can be revealed to other collaborating systems. For example, in accordance with the present invention, a one-way data structure such as a bloom filter may be used to store information related to a threat and for correlating detected alerts. Because one-way data structures such as bloom filters can be written to with data and checked to determine whether specifically known data has been previously written, but cannot be read to reveal what data has been written, these structures can be provided to other collaborating systems without revealing the information contained therein. Other types of data structures that do reveal such information may also be used when appropriate. When alerts are correlated, the alert correlator may indicate a threat. Any suitable response to the threat may then be taken, and information about the threat may be provided to other collaborating systems. This information may include a “profile” of the attack that enables the recipient of the information to infer the intent of the attacker and respond accordingly. 
         [0009]    The alert distributor uses an efficient technique to group collaborating systems and then pass data between certain members of those groups according to a schedule. In this way data can be routinely distributed without generating excess traffic loads. For example, the alert distributor may be used to exchange one-way data structures (e.g., bloom filters) or non-one-way data structure between collaborating systems. When such structures are received, the structures may be compared to determine whether there is a correlation of alert information between data structures. If there is, a threat may be indicated and any suitable action taken. For example, other collaborating systems may be alerted to the presence of the threat. 
         [0010]    In one embodiment, the invention provides a method for detecting a threat to a computer, comprising: detecting a first intrusion attempt; storing information related to the first intrusion attempt in a one-way data structure; detecting a second intrusion attempt; checking the one-way data structure to determine whether stored information related to the first intrusion attempt correlates with the second intrusion attempt and indicating that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
         [0011]    In a second embodiment, the invention provides a method for detecting a threat to a computer, comprising: receiving a one-way data structure from a collaborating system that contains information related to a first intrusion attempt; detecting a second intrusion attempt; checking the one-way data structure to determine whether stored information related to the first intrusion attempt correlates with the second intrusion attempt; and indicating that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
         [0012]    In a third embodiment, the invention provides a method for detecting a threat to a computer, comprising: receiving a data structure from a collaborating system that contains information related to a first intrusion attempt; receiving an indication of a characteristic of the collaborating system; detecting a second intrusion attempt; checking the data structure to determine whether stored information related to the first intrusion attempt correlates with the second intrusion attempt; and, based on the characteristic of the collaborating system, indicating that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
         [0013]    In a fourth embodiment, the invention provides a system for detecting intrusion attempts, comprising: an intrusion detection system that detects a first intrusion attempt and a second intrusion attempt; and an alert correlator that receives information related to the first intrusion attempt, that stores the information in a one-way data structure, that checks the one-way data structure to determine whether stored information related to the first intrusion attempt correlates with the second intrusion attempt, and that indicates that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
         [0014]    In a fifth embodiment, the invention provides a system for detecting intrusion attempts, comprising: an alert distributor that receives a one-way data structure from a collaborating system, wherein the one-way data structure contains stored information relating to a first intrusion attempt; an intrusion detection system that detects a second intrusion attempt; and an alert correlator that receives information related to the second intrusion attempt, that checks the one-way data structure to determine whether the stored information related to the first intrusion attempt correlates with the second intrusion attempt, and that indicates that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
         [0015]    In a sixth embodiment, the invention provides a system for detecting intrusion attempts, comprising: an alert distributor that receives a data structure from a collaborating system wherein the data structure contains stored information relating to a first intrusion attempt, and that receives an indication of a characteristic, of the collaborating system; an intrusion detection system that detects a second intrusion attempt; and an alert correlator that receives information related to the second intrusion attempt, that checks the data structure to determine whether the stored information related to the first intrusion attempt correlates with the second intrusion attempt, and that, based on the characteristic of the collaborating system, indicates that a threat is present when the stored information related to the first intrusion attempt correlates with the second intrusion attempt. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0016]    The present invention is now illustrated in connection with the accompanying drawings in which like references refer to like parts throughout and in which: 
           [0017]      FIG. 1  is a block diagram of a system for implementing, certain embodiments of the present invention; 
           [0018]      FIG. 2  is a block diagram of a collaborating system in accordance with certain embodiments of the present invention; 
           [0019]      FIG. 3  is an illustration of a bloom filter in accordance with certain embodiments of the present invention; 
           [0020]      FIG. 4  is a flow diagram showing one example of converting an IP address to a set of hash values in accordance with certain embodiments of the present invention; 
           [0021]      FIG. 5  is a flow diagram showing one example of converting a set of hash values to indexes to a bloom filter in accordance with certain embodiments of the present invention; 
           [0022]      FIG. 6  is an illustration of a table showing an example of different types of bloom filters and corresponding inputs that may be used in accordance with certain embodiments of the present invention; 
           [0023]      FIG. 7  is a flow diagram of an alert correlator process in accordance with certain embodiments of the present invention; 
           [0024]      FIG. 8  is a flow diagram of a bloom filter checking process in accordance with certain embodiments of the present invention; 
           [0025]      FIG. 9  is a flow diagram of a bloom filter insertion process in accordance with certain embodiments of the present invention; 
           [0026]      FIG. 10  is a block diagram of an alert distributor process in accordance with certain embodiments of the present invention; 
           [0027]      FIG. 11  is an illustration, of different states of an alert distributor process in accordance with certain embodiments of the present invention; 
           [0028]      FIG. 12  is a flow diagram of an alert distributor process in accordance with certain embodiments of the present invention; and 
           [0029]      FIG. 13  is a flow diagram of a process for processing bloom filters received from an alert distributor process in accordance with certain embodiments of the present invention. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0030]      FIG. 1  illustrates one embodiment of a system  100  in which the present invention may be implemented. As shown, system  100  includes multiple collaborating computer systems  102 ,  104 , and  106 , a communication network  108 , a malicious/compromised computer  110 , and communication links  112 . 
         [0031]    Collaborating systems  102 ,  104 , and  106  may be systems owned, operated, and/or used by universities, businesses, governments, non-profit organizations, families, individuals, and/or any other suitable person and/or entity. As set forth more fully in connection with  FIG. 2 , collaborating systems  102 ,  104 , and  106  may include any number of user computers, servers, firewalls, routers, switches, gateways, wireless networks, wired networks, intrusion detection systems, alert correlator systems, alert distributor systems, and any other suitable devices. Any number (including only one) of collaborating systems  102 ,  104 , and  106  may be present in system  100 , and systems  102 ,  104 , and  106  may be identical or different. 
         [0032]    Communication network  10  may be any suitable network for facilitating communication among computers, servers, etc. For example, communication network  108  may include private computer networks, public computer networks (such as the Internet), telephone communication systems, cable television systems, satellite communication systems, wireless communication systems, any other suitable networks or systems, and/or any combination of such networks and/or systems. 
         [0033]    Malicious/compromised computer  110  may be any computer, server or other suitable device for launching a computer threat such as a virus, worm, trojan, etc. The owner of malicious/compromised computer  110  may be any university, business, government, non-profit organization, family, individual, and/or any other suitable person and/or entity. The owner of computer  110  may not be aware of what operations computer  110  is performing or may not be in control of computer  110 . Computer  110  may be acting under the control of another computer or autonomously based upon a previous computer attack which infected computer  110  with a virus, worm, trojan, etc. Alternatively, computer  110  may be operated by an individual or organization with nefarious intent. Although only one malicious/compromised computer  110  is shown, any number of computers  110  may be present in system  100 . 
         [0034]    Communication links  112  may be any suitable mechanism for connecting collaborating systems  102 ,  104 , and  106  and malicious/compromised computer  110  to communication network  108 . Links  112  may be any suitable wired or wireless communication link, such as a T1 or T3 connection, a cable modem connection, a digital subscriber line connection, a WiFi or 802.11(a), (b), or (g) connection, a dial-up connection and/or any other suitable communication link. Alternatively, communication links  112  may be omitted from system  100  when appropriate, in which case systems  102 ,  104 , and/or  106  and/or computer  110  may be connected directly to network  108 . 
         [0035]    Turning to  FIG. 2 , one example of a collaborating system  102 ,  104 , and  106  (illustrated as collaborating system  102 ) is described in more detail. As shown, system  102  may include a firewall  200 , an internal network  202 , one or more computer device  204 , one or more intrusion detection systems  206  and  208 , an alert correlator  210 , an alert distributor  212 , and any other suitable device, or any subset of these devices. Firewall  200  may be any suitable hardware and/or software firewall as known in the art. Internal network  202  may be any suitable wired or wireless computer network, buss, communication link, etc. as known in the art. Computer devices  204  may be any suitable computer, server, personal digital assistant, handheld computer, wireless phone, other wireless device, or any other device or combination of devices. Intrusion detection system (IDS)  206  may be any suitable hardware and/or software for detecting intrusion attempts outside firewall  200 , such as Antura Recon from System Detection Inc., New York, N.Y. Intrusion detection system (IDS)  208  may be any suitable hardware and/or software for detecting intrusion attempts inside firewall  200 , such as a honey pot or an anomalous payload detection system as described in U.S. Patent Application Nos. 60/518,742 and 60/551,732, respectively filed Nov. 12, 2003 and Mar. 9, 2004, both of which are hereby incorporated by reference herein in their entirety. 
         [0036]    Alert correlator  210  and alert distributor  212  may be any suitable hardware and/or software for performing the functions described herein. For example, correlator  210  and distributor  212  may be implemented on personal computer executing the Linux operating system, a database, and software to implement the corresponding correlation and distribution functions described herein. As illustrated in  FIG. 2 , alert correlator  210  may receive input from IDS  206  and/or IDS  208 . By receiving input from IDS  206 , which is outside firewall  200  in system  102 , alert correlator  210  may be able to process all alerts that reach system  102 , not just alerts corresponding to those threats that pass through firewall  200 . Alerts that do pass through the firewall, or are generated internally to system  102 , may additionally or alternatively be detected by IDS  208  and passed to alert correlator  210 . 
         [0037]    As known in the art, the sub-systems  200 - 212  of system  102  may be implemented as separate devices or may be implement as functions being performed in one device, or any number of devices. 
         [0038]      FIGS. 3 ,  4 , and  5  illustrate example bloom filters and how they may be used in connection with the present invention. Although the present invention is illustrated in the figures as being implemented using bloom filters, any suitable one-way or non-one-way data structure may be used in accordance with the present invention. For example, in instances when keeping stored data (e.g., IP addresses) hidden is not critical, non-one-way data structures (e.g., trees, arrays, etc.) may be used in accordance with the invention. For example, government entities may not mind having IP addresses of potential attackers exchanged between them. In such cases, an array may be used instead of a bloom filter, and the IP address of a potential threat may be encoded (using a reversible technique) and used to index the array. The arrays may be filled with the same data that is stored in the bloom filter (e.g., zero, one, or a value representative of information related to a threat), and may be associated with the type of threat as shown in  FIG. 6 , as described below. 
         [0039]    As shown in  FIG. 3 , a bloom filter may be implemented as an N-bit word  310 . For example, N may be in the range of 2 15  to 2 20 . When first initialized, all bits  320  in the bloom filter may be set to zero. Based on the alerts that are detected, certain bits in the bloom filter (e.g., bits  2  and  6 ) may then be set to one. 
         [0040]    Turning to  FIGS. 4 and 5 , an example of steps for setting bits in a bloom filter based upon an input IP address are shown. As illustrated in  FIG. 4 , after an IP address 100.10.5.1 is received at step  410 , the components of the IP address may first be convened to hexadecimal form—i.e., 64.0A.05.01—at step  420 . These components may then be combined together to form one word—i.e., 640A0501—at step  430 . This combined word may than be hashed using any one or more hashing algorithms (as known in the art) at step  440 . For example, as shown, three hashing algorithms may be used. As illustrated, the outputs of the hashing algorithms may be any corresponding numbers—e.g., 150, 6234, and 15123—at step  450 . As illustrated in  FIG. 5 , these numbers (as shown at step  510 ) may be convened, to binary fbrm as 0000000010010110, 0001100001011010, and 0011101100010011, respectively (as shown at step  520 ). Next, different parts of these binary numbers may be selected for the bloom filter indexes (as shown at step  530 ). For example, as illustrated, alternating bits of the binary form of the number 150 may be selected to form an index 00001001, half of the bits of the binary number 6234 may be rearranged to form an index 00011010, and each nibble of the binary number 15123 may be rearranged to form an index 0011000110110011 These indexes may then be used to select bits to be set or reset in the bloom filter based upon whether a threat corresponding to the input data (e.g., an IP address) has been detected or not. 
         [0041]    By selecting multiple hashes of the same input and using multiple hash-bit-selection and hash-bit-rearrangement techniques, the bloom filters are more resilient to noise and data saturation. Although particular hash selection, hash-bit-selection, and hash-bit-rearrangement techniques are shown in  FIG. 5 , any suitable configuration of hash selection and hash-bit-selection and hash-bit-rearrangement techniques, including not rearranging the hash bits, may be used in accordance with the present invention. 
         [0042]    In certain embodiments of the present invention, it may be desirable to use different bloom filters for storing information for different purposes. For example, as shown in table  600  of  FIG. 6 , different bloom filters numbered 1 through n (see column  610 ) may be used to store alerts corresponding to all collaborating systems, bank collaborating systems, government collaborating systems, internal attacks, external attacks, port  80  attacks, scan alerts, non-scan alerts, login attacks, today&#39;s attacks, yesterday&#39;s attacks, and/or any other suitable characteristics of the exchanged alerts (see column  620 ). The inputs to these bloom filters may be the source IP address corresponding to an alert or threat, a signature corresponding to an alert or threat, or any other suitable data (see column  630 ). 
         [0043]    Although setting and resetting of bits in the bloom filters may be used to indicate the presence or non-presence of a threat, in certain embodiments of the invention, instead of setting and resetting bits, larger data values may also be used in the bloom filters to store information. For example, when no threat is present, the value may still be set to zero, but when a threat is present, the value may be set to the size of a datagram associated with the threat, the port number being targeted by the threat, a measure of the “stealthiness” of the threat, and/or any other suitable information. By properly encoding the values being stored, any suitable data or combination of data may be stored in a bloom filter. Obviously, using bit values in the bloom filter has the advantage of keeping the data structure smaller that if other size values were stored, thereby speeding-up data distribution. 
         [0044]    In this way, the present invention not only correlates attacks, but it also develops a “profile” of the attacks. This profile information may be useful to a collaborating system in inferring the intent of an attack and determining how to respond to a detected attack. For example, if a collaborating system is operated by a bank, and an attack has been detected from an IP address on other banks, but no other collaborating systems, the bank may respond by blocking all traffic from a corresponding. IP address at its firewall, contact suitable authorities, etc. Whereas with an attack that is being detected by a wide variety of types collaborating systems (e.g., banks, universities, and governments), the bank may simply decide to filter traffic based upon a signature of the threat. 
         [0045]      FIG. 7  illustrates a process  700  that may be performed by alert correlator  210 . As shown, after process  700  begins at step  710 , the process waits for and receives an alert at step  720  from IDS  206  or  208 . This may be accomplished by retrieving the alert from a database connected to or part of IDS  206  or IDS  208 . This alert may be generated by an IDS  206  or  208 , and may be indicative of any type of reconnaissance, attack, or anomalous activity. Once an alert has been received, process  700  may select one or more bloom filters corresponding to the alert at step  730 . For example, as illustrated in  FIG. 6 , one bloom filter may be provided for attacks on port  80 , another bloom filter may be provided for scan alerts, yet another bloom filter may be provided for all alerts, etc. By providing different bloom filters for different types of attacks, the bloom filter may be able to provide a “profile” of the attack that is, if a bloom filter indicates a possible attack, and the bloom filter is a “scan attack” bloom filter, the profile of the attack is known to include that the alert is a “scan attack.” Next at step  740 , process  700  may determine whether a corresponding alert has been previously entered in any of the selected bloom filters. An example of such a sub-process is described below in connection with  FIG. 8 . The check may be made to determine whether an alert is correlating with a previous alert from the same system or whether an alert is correlating with a previous alert from another system based, for example, on which bloom filters are selected. If the alert is determined to have been found in a bloom filter, at step  750 , process  700  branches to step  760  where any suitable response to an attack may be taken. For example, at step  760 , process  700  may attempt to defend its local system (e.g., system  102 ) from the attack by: alerting a system administrator of an attack; shutting-down firewall  200 ; blocking all traffic from the corresponding IP address; generating a firewall filter rule based on a datagram of the threat, a signature of the threat, an IP address of threat, the destination port targeted, and/or the datagram length associated with the threat; and/or performing any other suitable action known in the art. Process  700  may also attempt to help other collaborating systems (e.g., systems  104  or  106 ) defend against the attack by alerting other collaborating systems  104  and  106  of the attack by providing them with a firewall filter rule and/or information about the attack, such as the kind of attack (e.g., scanning, probing, etc.), a datagram of the threat, a signature of the threat, an IP address of the attack, the destination port/service targeted, the length of the datagram associated with the threat, type of other collaborating systems that have detected the threat, a measure of the “stealthiness” of the threat, and/or any other profile information related to the threat that may be useful in preventing, detecting, responding to, and/mitigating the effects of the attack. 
         [0046]    If the alert is determined not to have been found in a bloom filter, at step  750 , process  700  branches to step  770  where the alert is entered into the selected bloom filters. An example of such a sub-process is described below in connection with  FIG. 9 . 
         [0047]    Turning to  FIG. 8 , a sub-process  800  corresponding to step  740  for determining whether a corresponding alert has been previously entered in any of a set of selected bloom filters is shown. As illustrated, at step  810 , for each selected bloom filter, sub-process  800  selects the data to be used for that bloom filter. For example, for bloom filter  1  in  FIG. 6 , as shown in column  630 , the input data is the source IP address corresponding to the alert or threat. Next, at step  820 , sub-process  800  forms one or more hashes of the selected data. Any suitable hashing functions known in the art may be used in step  820 , such as SHA-1, MD-5, etc. Sub-process  800  then may select one or more parts of the hashes and, based on the selected parts of the hashes, determine which bits in the bloom filters need to be checked. The specific hash functions and parts of the hash functions to be used may be kept as a shared secret among the collaborating systems. Next, at step  840 , the bits in the bloom filters are checked, and if the bits are not already set, then sub-process  800  branches to step  860  which outputs that a corresponding alert has not been found in the bloom filters. Otherwise, sub-process  800  branches to step  850  which outputs that a corresponding alert has been found in the bloom filters. 
         [0048]    As shown in  FIG. 9 , a sub-process  900  corresponding to step  770  for inserting an alert into a bloom filter is illustrated. Beginning at step  910 , sub-process  900  selects the data to be used as inputs for the selected bloom filters. For example, for bloom filter  1  in  FIG. 6 , as shown in column  630 , the input data is the source  11 P address corresponding to the alert or threat. Next, at step  920 , hashes of this data are formed, as described above. Then, at step  930 , the sub-process selects one or more parts of the hashes and determines which bits in the bloom filter to set, as also described above. Finally, at step  940 , the determined bits are set in the bloom filters. 
         [0049]    As stated above, an alert distributor  212  may be used to distribute alert information, such as bloom filters, between collaborating systems. Although any suitable data distribution mechanism, such as a peer-to-peer network or a central server for storage and retrieval, may be used in accordance with the present invention, in order to securely and efficiently distribute this information, the distribution mechanism illustrated in  FIGS. 10-12  is preferably used. As shown in  FIG. 10 , any number of circular buffers  1010 - 1040  ma be used to form groups of collaborating systems. For example, buffer  1010  groups collaborating, systems  1 ,  2 ,  3 , and  4 , buffer  1020  groups collaborating systems  5 ,  6 ,  7 , and  8 , buffer  1030  groups collaborating systems  9 ,  10 ,  11 , and  12 , and buffer  1040  groups collaborating systems  13 ,  14 ,  15 , and  16 . Each collaborating system identified in the same position A, B, C, or D in buffers  1010 - 1040  is considered to be in the same family. For example, collaborating systems  1 ,  5 ,  9 , and  13  are in the same family, systems  2 ,  6 ,  10 , and  14  are in the same family, systems  3 ,  7 ,  11 , and  15  are in the same family, and systems  4 ,  8 ,  12 , and  16  are in the same family. At least once each unit time (which may be any suitable period of time, e.g., one second, two minutes, half hour, etc.), each member of a family exchanges alert information (e.g., bloom filters) with other members of that family. This exchange may be done using any suitable technique. In order to prevent false bloom filters from being distributed by nefarious computers, the bloom titters may be digitally signed by the senders and then verified by the recipients. 
         [0050]    Another circular buffer  1050  having as many positions as there are circular buffers  1010 - 1040  may be used to indicate the rotation rate for buffers  1010 - 1040 . For example, as shown, circular buffer  1050  has four positions corresponding to the four circular buffers  1010 - 1040 , and these positions are filled with numbers 1, 2, 4, and 8 indicating that buffers  1010 ,  1020 ,  1030 , and  1040  will advance one position every 1, 2, 4, and 8 units time, respectively. Obviously, any suitable rotation rates could be used in accordance with the present invention. For example, buffer  1040  may be advanced one position every ten units time, buffer  1030  may be advanced one position every nine units time, buffer  1020  may be advanced one position every eight units time, and buffer  1010  may be advanced one position every seven units time. Preferably, the rotation schedule is difficult to guess or predict. Each time the least frequently rotating buffer (e.g., buffer  1040 ) has completed a full rotation and returned to its original order, circular buffer  1050  will advance one position to cause the next buffer (e.g., buffer  1010 ) to become the least frequently rotating buffer. 
         [0051]    Turning to  FIG. 11 , an illustration of the rotation process is shown. As can be seen, circular buffers  1010 - 1040  are in their original positions in state  1110 . Next at state  1120 , circular buffer  1010  has advanced one position. At state  1130 , circular buffer  1010  has rotated a total of two positions and buffer  1020  has advanced one position. Next at state  1140 , circular buffer  1010  has rotated a total of three positions. At state  1150 , circular buffer  1010  has completed a full rotation and returned to its original position, circular buffer  1020  has advanced a total of two positions, and circular buffer  1030  has advanced one position. This process continues through states  1160 ,  1170 ,  1180 ,  1190 , and other states not shown until circular buffers  1010 - 1040  return to the positions shown in state  1110 , at which point the process repeats itself. 
         [0052]    Although  FIGS. 10 and 11  illustrate four circular buffers  1010 - 1040 , each containing four positions, any suitable number of circular buffers containing any suitable number of positions may be used in accordance with the present invention. For example, N (e.g., nine) circular buffers may be used, and each buffer may contain √N (e.g., three) positions. Moreover, although circular buffers are described herein, any suitable data structure that facilitates associating groups and families of collaborating systems may be used in accordance with the invention. 
         [0053]    This distribution process is illustrated as a process  1200  in  FIG. 12 . Beginning at step  1210 , process  1200  assigns each collaborating system to one of N circular buffers, each having a position A through M. This assignment may be performed, for example, by performing a hash function on each collaborating; system&#39;s IP address to provide a circular buffer number to which the collaborating system should be assigned. Next, at step  1220 , at each unit time, process  1200  exchanges bloom filters between all collaborating systems in the same positions A through M. In order to prevent false bloom filters from being distributed by nefarious computers, the bloom filters may be digitally signed by the senders and then verified by the recipients. Then at step  1230 , process  1200  rotates each circular buffer according to the corresponding schedule for that buffer. Finally, at step  1240 , when all circular buffers have rotated back to their original positions, process  1200  rotates the schedule for rotating, the N circular buffers and returns to step  1220 . 
         [0054]    To further protect the security and anonymity of the data being exchanged by the collaborating systems, a central authority may operate a trusted proxy server or other data exchange mechanism that is used to exchange data between the systems. In this way, no collaborating system would be able to determine the IP address of a collaborating system from which it is receiving information. In such a case, however, the central authority may assign and the collaborating systems may know the category or type of system (e.g., a bank, university, government, etc.) with which it is exchanging data. This category may be based on SIC codes or any other suitable mechanism. In this way, the systems would be better able to evaluate a profile of a threat and thereby infer the intent of the threat. The central authority may also assign encryption keys used by the collaborating systems. Furthermore, the central authority may provide the same alert correlation and alert distribution functions described herein as being performed by the collaborating systems. In such a case, it may not be necessary to hide data (e.g., IP addresses of possible threats) being provided to the central authority by each collaborating system because the authority is trusted to maintain that data in confidence. 
         [0055]      FIG. 13  is a flow diagram of a process  1300  that may be used to process bloom filters received at a collaborating system by way of an alert distributor. As shown, at step  1310 , process  1300  waits for a bloom filter to be received. These bloom filters may replace bloom filters previously received from the same source collaborating system. These bloom filters may also be checked as part of the process illustrated in  FIGS. 7 and 8 . Next, at step  1320 , the process compares pairs of bloom filters of the same type for like alerts by performing a logical “AND” operation. Any resulting set bits may indicate a potential threat. As step  1330 , process  1300  determines whether any bloom filter hits correlate, and if not, the process loops back to step  1310 . Otherwise, process  1300  branches to step  1340  where an attack may be indicated using any suitable technique as described above. For example, a collaborating system may attempt to defend its local system (e.g., system  102 ) from the attack by: alerting a system administrator of an attack; shutting-down firewall  200 ; blocking all traffic from the corresponding IP address; generating a firewall filter rule based on a datagram of the threat, a signature of the threat, an IP address of threat, the destination port targeted, and/or the datagram length associated with the threat; and/or performing any other suitable actions known in the art. A collaborating system may also attempt to help other collaborating systems (e.g., systems  104  or  106 ) defend against the attack by alerting other collaborating systems  104  and  106  of the attack by providing them with a firewall filter rule and/or information about the attack, such as the kind of attack (e.g., scanning, probing, etc.), a datagram of the threat, a signature of the threat, an IP address of the attack, the destination port/service targeted, the length of the datagram associated with the threat, type of other collaborating systems that have detected the threat, a measure of the “stealthiness” of the threat, and/or any other profile information related to the threat that may be useful in preventing, detecting, responding to, and/mitigating the effects of the attack. 
         [0056]    In order to prevent false alerts due to bloom filter saturation, the filters may be periodically cleared. Alternatively, instead of using bits with a value of one to represent specific alerts, the bloom filters may use a time value representative of the date or time that an alert has been detected. Then, over time, the value may be updated when a correlating alert is detected or the value may be set to zero when no correlating alert is detected. When suitable, the time value may be combined with other data in the bloom filter and decoded as appropriate. 
         [0057]    Although the present invention has been described and illustrated in the foregoing exemplary embodiments, it is understood that the present disclosure has been made only by way of example, and that numerous changes in the details of implementation of the invention may be made without departing from the spirit and scope of the invention, which is limited only by the claims which follow.