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....It is therefore of great importance to characterize and monitor the spread of active worms, and be able to derive methods to effectively defend our systems against them. About ten years ago, Kephart and White presented the Epidemiological model to understand and control the prevalence of viruses [6], 7] 8] This model is based on biological epidemiology and uses nonlinear differential equations to provide a qualitative understanding of virus spreading. White pointed out, however, that the mystery of the Epidemiological model Zesheng Chen was with the Department of Electrical Computer ....
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Jeffrey Kephart and Steve White. Measuring and modeling computer virus prevalence. In Proceedings of 1993 IEEE Symposium on Security and Privacy, pages 2--15. IEEE Computer Society Press, May 1993.
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....it does not pass along the signal, but at least it has received the database updates effectively immunizing it against that virus (see Fig. 2) Theoretical modeling has shown the kill signal to be extremely effective, particularly in topologies that are highly localized or sparsely connected [4, 11]. Kill Signals t=1 t=3 t=2 Immune ( kill signal) Infected Susceptible Immune Figure 2: Fighting self replication with self replication. When a computer detects a virus, it eliminates the infection, immunizes itself against future infection, and sends a kill signal to its neighbors. Receipt of ....
Kephart, Jeffrey O. and Steve R. White. Measuring and modeling computer virus prevalence. Proceedings of the 1993 IEEE Computer Society Symposium on Research in Security and Privacy. Oakland, California, May 24--26, 1993, 2--15.
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