textfiles/virus/hormones.vir

Date: Thu, 16 Mar 89 20:56:18 +0100
From: David Stodolsky <stodol@diku.dk>

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. [<davidf@CS.HW.AC.UK> <Fri, 10 Feb 89 
11:45:37 GMT>]

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 
<pjs@grouch.jpl.nasa.gov>. <Fri, 10 Feb 89 10:46:21 PST>]

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                          diku.dk!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