P $^{2}$ CySeMoL: Predictive, Probabilistic Cyber Security Modeling Language
Hannes Holm, Khurram Shahzad, Markus Buschle, Mathias Ekstedt · IEEE Transactions on Dependable and Secure Computing · 2014
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.