Using Centrality Measures in Dependency Risk Graphs for Efficient Risk Mitigation

Cascading failures of Critical Infrastructures (CIs) can be modeled through Dependency Risk Graphs, in order to assess the expected risk of CI dependency chains. In this paper we extend our previous dependency risk analysis methodology towards risk management. We explore the relation between dependency risk paths and graph centrality measures, in order to identify nodes that significantly affect the overall dependency risk. We experiment using 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 define priorities in selecting nodes for the application of mitigation controls, in order to achieve efficient risk mitigation.