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Meta Description: A natural epidemic is a disease that suddenly affects many individuals in a short time period, spreading from person to person in a locality where the disease is not usually prevalent. The sudden outbreak of an epidemic is usually modeled as a random variable because it cannot be anticipated. Epidemics introduced by bioterrorists are planned events by intelligent adversaries, who might also introduce other terrorists’ activities that depend on the responses of the defenders.
Since these events are not random, models maybe helpful for anticipating terrorist attacks. Since defending against such attacks does not fit into the classical modeling paradigm because there is a scarcity of data, the defender must respond quickly, the attacker can also adapt new strategies in response to the actions of the defender, new modeling strategies are required to improve the strategies of the defender.
Model combined with fault trees is proposed for determining sequential optimal defense strategies for the defender by identifying minimal cut sets of events that would most likely lead to a successful terrorist attack. Further, if the model can be formulated as a sequence of state changes based on default trees, a dynamic programming problem with the Bellman equation reduces the solution from evaluating a complex model to evaluating a sequence of simple problems
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