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Abstract:
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Attack graphs are a tool to evaluate the security of the network as a whole rather than looking at individual machines. They can discover ``foothold'' situations where an attacker compromises a series of machines to use as a platform within the network to achieve the final goal(s). Attack graphs are visually complex for all but the smallest networks. Analyzing the graphs to determine a set of actions to take would provide administrators with a plan of action to secure a system. However, determining the minimal set of hardening measures is a reduction of the set cover problem and thus NP. This work explores the use of genetic algorithms to determine a set of hardening measures that maximize the security benefit while minimizing the cost.
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