Evaluating Interdependencies and Cascading Failures Using Distributed Attack Graph Generation Methods for Critical Infrastructure Defence

Abstract

Attack graphs facilitate modelling, detection and analysis of networks, along with providing the functionality to identify potential vulnerabilities and risks within networked systems. When attack graphs are applied to large heterogeneous collaborative infrastructures i.e. Systems-of-Systems (such as critical infrastructures), existing schemas struggle to detect and evaluate interdependencies and cascading failures. The failings of these existing schemas include but are not limited to, the inability to accurately ascertain the relationships and interdependencies between risks, to adequately identify and visualise the consequences of identified risks, and the inability to reduce attack graph size and generation complexity. Having simulated a city based on real-world scenarios and critical infrastructures, we can visualise the effects of cascading failure. Data extracted from the simulation will be used to evaluate our schema, and will assist in the analysis of the potential consequences of component and system failures. We discuss the benefits of a distributed schema which utilises attack graph generation methods, which provides a means for collaborative interdependent systems to be fully analysed, along with assisting in the identification of interdependencies and cascading failures which will be visualised and reported.