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FTP'd from File pub/virus-l/docs/net.hormones Date: Thu, 16 Mar 89 20:56:18 +0100 From: David Stodolsky Net Hormones: Part 1 - Infection Control assuming Cooperation among Computers Copyright (c) 1989 David S. Stodolsky, PhD. All rights reserved. 1. Abstract A new type of infection control mechanism based upon contact tracing is introduced. Detection of an infectious agent triggers an alerting response that propagates through an affected network. A result of the alert is containment of the infectious agent as all hosts at risk respond automatically to restrict further transmission of the agent. Individually specified diagnostic and treatment methods are then activated to identify and destroy the infective agent. The title "Net Hormones" was chosen to indicate the systemic nature of this programmed response to infection. 2. Introduction A new type of infection control mechanism that is based upon network- wide communication and that depends upon cooperation among computer systems is presented. Neither diagnosis nor treatment is necessary for the operation of the mechanism. The mechanism can automatically trigger responses leading to effective containment of an infection. The identification and destruction of the infectious agent is determined by individual actions or programs. This permits a highly desirable heterogeneity in diagnostic and treatment methods. Definition: "Hormone . . . 1: a product of living cells that circulate in body fluids or sap and produces a specific effect on the activity of cells remote from its point of origin; especially one exerting a stimulatory effect on a cellular activity. 2: a synthetic substance that acts like a hormone (Webster's new collegiate dictionary, 1976)." The analogy here is between each network node or computer system and the cell. In biological systems hormones attach to specialized receptors on the cell surface resulting in cell activation. In the system described here, a match between a code in a system archive and a code delivered as part of an alerting message results in activation. Alerting messages circulated electronically serve the role of hormones. Epidemiology has traditionally had three major approaches to the control of infectious agents: :1 - Treatment of the sick (e. g., penicillin) :2 - Contact tracing (e. g., social-work notification programs, laws forcing the reporting of certain diseases and of contacts of infected persons) :3 - Prevention (e. g., vaccination, public information campaigns) In computer system terms: :1 - Treatment of infections (e. g., various programs and manually installed patches and fixes) :2 - Contact tracing (e. g., software "recall", and other manual operations) :3 - Prevention (e. g., various programs for blocking virus replication, alerting users, and for logging suspicious events) Contact tracing has been neglected with computer systems, although it could be argued it is much easier with computer systems than with biological systems. Currently such tracing depends upon people reading reports and determining if their system is subject to infection, performing diagnostic tests, determining a treatment method, obtaining software, and so on. This is chancy and time consuming, requiring most often people with the highest level of expertise. As computers and networks speed up, an infectious agent could spread through a network in hours or minutes. "Once a virus has infected a large number of computers on a network, the number of infected removable media elements will begin to skyrocket. Eventually, if the virus continues to go undetected, a stage is reached in which the probability of identifying and recovering all of the infected media is virtually zero (McAfee, 1989)." An automated contact tracing system thus seems essential in the future if infectious agents are to be controlled. 3. Threats "The modification of an existing virus to incorporate a long term delay (such as 6 months or even a year) coupled with a totally destructive manipulation task (such as a FAT, Boot sector scribble followed by a complete format) is a fairly simple task. Such an action would convert even a crude virus strain such as the Lehigh 1 virus into a devistating (sic) strain. (Eg the comment by Ken that the modified version of the Lehigh virus is now far more dangerous due to modification of the delay in activation of its manipulation task) (Ferbrache, 1989)." Scott (1989) requested comments on: "A little future speculation here... currently we seem to be fighting a losing battle against virus detection and as viruses improve it's unlikely that that will change. If we want the capability to download shareware, etc, from bulletin boards, etc, then we must assume that we cannot check the software for a virus with 100% success before running it. In general, you can't know the output of a program given the input without running it, except in special cases. We can check for *known* viruses; but how long before shape-changing and mutating viruses hit the scene that defeat all practical recognition techniques?" An inapparent infection could spread rapidly, with damage noted only much later. Consider a worm that is constructed to carry a virus. The worm infects a system, installs the virus and then infects other nearby systems on the net. Finally, it terminates erasing evidence of its existence on the first system. The virus is also inapparent, it waits for the right moment writes some bits and then terminates destroying evidence of its existence. Later the worm retraces its path reads some bits, then writes some bits and exits. The point is that an inapparent infection could spread quite widely before it was noticed. It also might be so hard to determine whether a system was infected or not, that it would not be done until damage was either immanent or apparent. This analysis suggests response to network-wide problems would best be on a network level. 4. Theory of operation Computers generate (in the simplest case) random numbers which are used to label transactions. A transaction is defined as an interaction capable of transmitting an infectious agent. After each transaction both systems therefore have a unique label or code for that transaction. In the event that a system is identified as infected, the transaction codes which could represent transactions during which the agent was transmitted are broadcast to all other computers. If a receiving computer has a matching code, then that system is alerted to the possibility of the agent's presence, and can broadcast transaction codes accumulated after the suspect contact. This iterates the process, thus identifying all carriers eventually. The effect is to model the epidemiological process, thereby identifying all carriers through forward and backward transaction tracking (Stodolsky, 1979a; 1979b; 1979c; 1983; 1986). 5. The process of infection control The process can be broken down into routine and alerting operations. During routine operations, each file transfer is labeled in a way that does not identify the systems involved. These labels are time stamped (or have time stamps encoded in them). They are written into archives on each system, ideally write-once/read-many times devices or some other type of storage that could not easily be altered. Alerting procedures are invoked when an infectious agent is noted or when a suspect transaction code is received that matches one in the system's archive. The earliest time the agent could have arrived at the system and latest time (usually the moment the agent is noted or a received suspect transaction code is matched) it could have been transmitted from the system are used to delimit suspect transaction codes. These codes are broadcast to alert other systems to the potential presence of the agent. In the simplest and most common case, if a system gets an alert that indicates, "You could have been infected at time one," then the system automatically packages the transaction codes between time one and the present time to generate a new alert indicating the same thing to other systems with which it has had contact. Another automatic response could be to immediately cut off communications in progress, thus reducing the risk of infection. A further benefit of such a reaction would be the possibility of disrupting the transfer of an infectious agent. Such a disrupted agent would be harmless and easily identified and evaluated. Reestablishment of communication could occur immediately with new procedures in force that could warn new users that an alert was in progress as well as limiting the type of transfers that could take place. 5.1. Practical considerations Direct identification, as opposed to identification through forward tracing notification, does not delimit effectively the earliest time that an agent could have been present on a system. Thus an alert from an originating system could include all transaction codes written prior to the identification (or some default value). This could generate excessive reaction on the network. This reaction could be controlled if another system in a later alert indicated it had originated the infection on the system originating the alert. Thus, protection of identity which reduces any inhibition about reporting infection is important. The type of reaction discussed here might be called a panic reaction, because an excessive number of systems might be notified of potential infection in the first instance. A more restricted response could be generated if persons at the alert originating system analyzed the causative agent, thereby hopefully establishing the earliest time the agent could have been present on that system. In this case, the suspect transactions could be delimited effectively and all systems that could have been infected would be notified, as would the system that had transmitted the agent to the system originating the alert (assuming one exists). Ideally, each notified system would be able to determine if it had received or originated the infection and respond accordingly. 5.2. Forward tracing assumption Assume, however, that rapid response is desired. Each notified system would then react as if it had been notified of an infection transmitted to it. It would package the transaction codes that had been written later than the suspect transaction code it had received and issue a secondary alert. This forward tracing assumption would lead to quite effective control because of the exponential growth in the number of infected hosts in epidemics (and exponential growth of alerts resulting >From forward tracing). That is, a system can infect many others as a result of a single infective agent transmitted to it. Forward tracing would alert all systems that the alerting system could have infected. These newly alerted systems would also issue forward trace alerts, and this would continue until containment was reached under the forward tracing assumption. 5.3. Backward tracing of suspect contacts and diagnosis As a result of this rapid forward tracing response, it is likely that more active infections would be identified. The resulting new information could be used to more effectively characterize the life cycle of the agent, thereby hopefully permitting effectively delimited backward tracing. Also as a result of accumulated information, positive tests for the agent would become available. Once this stage had been reached the focus of action could shift from control of suspect transactions to control of transactions known to facilitate the transmission of the agent. 6. Feasibility and Efficiency Both technical and social factors play a key role in the operation of the control mechanism. Contact tracing is probably most effective for sparsely interacting hosts. The rate of transfer of the infectious agent as compared to the rate of transfer of the suspect transaction codes is also a critical factor. Recording of transactions can be comprehensive on computer networks, however, unregistered transactions will be a factor in most cases. Once the infectious agent has been identified, the type of transactions capable of transmitting the agent can be delimited. This could increase efficiency. 6.1. Social organization of alerts Another major efficiency factor is errors in origination of alerts. Since protected messages would trigger network-wide alerts, it is important that false alarms are controlled effectively. On the other hand, failure to report an infection could permit an infectious agent to spread in an uncontrolled manner and could increase the number of systems unnecessarily alerted. Successful operation of the mechanism described above assumes voluntary cooperation among affected systems. This assumption could be relaxed by application of an enforcement mechanism. It would require substantially greater complexity and greater centralization of coordination. In other words, if cooperation was not forthcoming "voluntarily", users would likely be treated to a complicated, restrictive, and resource intensive mechanism that would be developed to enforce it. "Estimates of the damages inflicted by November's Internet infection alone ranged upward of $100 million . . . (McAfee, 1989)." Costs of this magnitude make it very likely that even expensive enforcement mechanisms will be developed if they are made necessary. The simplest organizational strategy would assume that protection of identity was not needed, but this would also be likely to inhibit alerting. True anonymity, however, permits irresponsible behavior to go unchecked. A reputation preserving anonymity (pseudonymity) would be desirable to ensure both protection and accountability and thereby promote cooperation. Pseudonyms would best be the property of persons (in association with a computer system). Even sincere cooperation, however, would not eliminate inefficiencies resulting from false alarms or failure to alert. Both inadequate training and poor judgement are likely sources of these errors. If users realize that there are reputational costs associated with these failures, then they are likely to be motivated to minimize them. False alarms are already a major problem because of user inexperience and the high level of defects in widely used software. A reputational mechanism would motivate increased user education and more careful software selection, with a corresponding pressure on software publishers to produce well behaved and carefully documented products. 6.2. Enforcing cooperation Crypto-protocols could be used to ensure that a non-cooperator could not communicate freely with others using the infection control mechanism. This type of communication limiting could be used routinely to ensure that a system requesting connection was not infected. In effect, systems would exchange health certificates before file exchanges, to ensure that they would not be infected. A system that could not show a health certificate could be rejected as a conversation partner due to risk of infection. This would no doubt enforce cooperation. The mechanism (Stodolsky, 1986) is beyond the scope of this note. 6.3. Non-network transfers While the discussion above has focused on transfers through networks, the same principles could be applied to disk or tape transfers. The originating system would write a transaction code on the medium with each file. Protection of identity would possibly be reduced under this type of transfer. Since there is no question about the directionality of transmission of an infectious agent in off-line transfers, non- network transmission is likely to be easier to control. Several other factors, such as the rate of spread of the agent, are likely to make such infections less troublesome. 7. Summary and Benefits The idea behind Net Hormones is to make immanent danger apparent. More precisely Net Hormones permit the visualization of infection risk. 7.1. Control of unidentified infectious agents. Net Hormones work by permitting isolation of infectious hosts from those at risk. Identification of the infectious agent is not required for action. Therefore, new and as yet unidentified agents can be effectively controlled. 7.2. Rapid response Hosts could automatically respond to alerts by determining if they had been involved in suspect contacts, and generate new alerts that would propagate along the potential route of infection. 7.3. Protection of identity The mechanism could function without releasing the identity of an infected host. This could be crucial in the case an institution that did not wish it to be publicly know that its security system had been compromised, or in the case of use of unregistered software. More precisely, software obtain by untraceable and anonymous file transfers could be protected by this mechanism without release of users' identity. 7.4. Distributed operation Operation is not dependent upon a centralized register or enforcement mechanism. Some standardization would be helpful, however, and a way to broadcast alerts to all potential hosts would be valuable. 8. References Ferbrache, David J. (1989, February 10). Wide area network worms. VIRUS-L Digest, V. 2 : Issue 44. [ ] McAfee, J. D. (1989, February 13). In depth: Managing the virus threat. Computerworld, 89-91; 94-96. Scott, Peter. (1989, February 10). Virus detection. VIRUS-L Digest, V. 2 : Issue 44. [PJS%naif.JPL.NASA.GOV@Hamlet.Bitnet . ] Stodolsky, D. (1979a, April 9). Personal computers for supporting health behaviors. Stanford, CA: Department of Psychology, Stanford University. (Preliminary proposal) Stodolsky, D. (1979b, May 21). Social facilitation supporting health behaviors. Stanford, CA: Department of Psychology, Stanford University. (Preliminary proposal) Stodolsky, D. (1979c, October). Systems approach to the epidemiology and control of sexually transmitted diseases. Louisville, KY: System Science Institute, University of Louisville. (Preliminary project proposal) Stodolsky, D. (1983, June 15). Health promotion with an advanced information system. Presented at the Lake Tahoe Life Extension Conference. (Summary) Stodolsky, D. (1986, June). Data security and the control of infectious agents. (Abstracts of the cross disciplinary symposium at the University of Linkoeping, Sweden: Department of Communication Studies). Webster's new collegiate dictionary. (1976). Springfield, MA: G. & C. Merriam ------------------------------------------------------------- David Stodolsky!stodol@uunet.UU.NET Department of Psychology Voice + 45 1 58 48 86 Copenhagen Univ., Njalsg. 88 Fax. + 45 1 54 32 11 DK-2300 Copenhagen S, Denmark stodol@DIKU.DK


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