Risk mitigation strategies for critical infrastructures based on graph centrality analysis

Dependency Risk Graphs have been proposed as a tool to analyze the cascading failures of Critical Infrastructure (CI) dependency chains. However, dependency chain analysis is not by itself sufficient for developing an efficient risk mitigation strategy, i.e. a strategy that defines which CI nodes should have high priority for the application of mitigation controls, in order to achieve the optimal overall risk reduction. In this paper we extend our previous dependency risk analysis methodology towards efficient risk mitigation, by exploring the relation between dependency risk paths and graph centrality characteristics. We explore how graph centrality metrics can be applied to design and to evaluate the effectiveness of risk mitigation strategies. We examine alternative mitigation strategies and we empirically evaluate them through simulations. Our experiments are based on random graphs that simulate common CI dependency characteristics, as identified by recent empirical studies. Based on our experimental findings, we propose an algorithm that can be used to prioritize CI nodes for the application of mitigation controls, in order to achieve an efficient risk mitigation. ∗Corresponding author Email addresses: [email protected] (George Stergiopoulos), [email protected] (Panayiotis Kotzanikolaou), [email protected] (Marianthi Theocharidou), [email protected] (Dimitris Gritzalis) Preprint submitted to International Journal of Critical Infrastructure Protection May 4, 2015