Probabilistic reasoning with graphical security models

摘要: We develop a framework for probabilistic analysis of security scenarios with dependencies.We combine the model attack-defense trees (ADTrees) Bayesian networks.We prove that propositionally equivalent ADTrees yield same probability value.We compare our computational method standard bottom-up algorithm ADTrees.We use semiring theory to improve efficiency computations. This work provides meaningful evaluation involving dependent actions. graphical modeling technique information expressed in terms networks. In order computations on trees, we make inference algorithms and encoding techniques from constraint reasoning. The proposed approach is illustrated running example are automated help suitable software tools. show routines developed this paper form conservative generalization tree formalism defined previously. discuss algebraic underlying point out several generalizations which possible thanks theory. Finally, results apply directly industrially recognized attack trees.