Abstract
Attack graphs are a formalism for capturing the most important ways to compromise a system. They are used for evaluating risks and designing appropriate countermeasures. Analysis of attack graphs sometimes requires computing the optimal attack strategy that minimizes the expected cost of the attacker in case of stochastically failing actions. We point out several results in AI literature that are highly relevant to this problem, but remain unnoticed by security literature. We note the problem has been shown to be NP-hard and we present how the problem can be reduced to the problem of solving an unconstrained influence diagram (UID). We use an existing UID solver to assess the scalability of the approach, showing that it can be used to optimally solve attack graphs with up to 20 attack actions.
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Lisý, V., Píbil, R. (2013). Computing Optimal Attack Strategies Using Unconstrained Influence Diagrams. In: Wang, G.A., Zheng, X., Chau, M., Chen, H. (eds) Intelligence and Security Informatics. PAISI 2013. Lecture Notes in Computer Science, vol 8039. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39693-9_5
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DOI: https://doi.org/10.1007/978-3-642-39693-9_5
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