Using game theory to mitigate the effects of a bioterrist attack.

摘要

The goal of our work was to apply proven human-oriented situation analysis with existing simulation techniques to explore new ways of enhancing security through anticipation of human thought processes and activity. In particular, we used social networking to model relationships and game theory to model motivations of those participating. The end result of these studies yielded a combination of methods to anticipate, plan for, and reduce the impact of a biological attack. The SIR model was modified and applied to an individual-level social network through the use of theatres and approximated influences due to relationships, creating a unique, high performance mathematical model to observe the spread of disease. This model was then simulated in a number of scenarios spanning the use of possible biological attack situations, inoculations, and several novel intervention methods. The results of the simulation were then analyzed as a Stackelberg game in order to search for a lower bound to the expected costs and loss of human life under the assumption that the attacker goes last.