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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