P CySeMoL: Predictive, Probabilistic Cyber Security Modeling Language

This paper presents the Predictive, Probabilistic Cyber Security Modeling Language (P²CySeMoL), an attack graph tool that can be used to estimate the cyber security of enterprise architectures. P²CySeMoL includes theory on how attacks and defenses relate quantitatively; thus, users must only model their assets and how these are connected in order to enable calculations. The performance of P²CySeMoL enables quick calculations of large object models. It has been validated on both a component level and a system level using literature, domain experts, surveys, observations, experiments and case studies.