Decision Networks for modeling and analysis of attack/defense scenarios in critical infrastructures

We propose to exploit Decision Networks (DN) for the analysis of attack/defense scenarios. We show that DN extend both the modeling and the analysis capabilities of formalisms based on Attack Trees, which are the main reference model in such a context. Uncertainty can be addressed at every system level and a decision-theoretic analysis of the risk and of the selection of the best countermeasures can be implemented, by exploiting standard inference algorithms on DN.