Graph-theoretic algorithms for cyber-physical vulnerability analysis of power grid with incomplete information

A key focus recently has been in assessing the risk of a coordinated cyber-physical attack and minimizing the impact of a successful attack. Most of the cyber-attackers will have limited system information and conventional power grid N − 1 security analysis cannot be extended to assess the risk. Centrality measures are widely used in the network science and an attacker with incomplete information can use it to identify power system vulnerabilities by defining the system as a complex network but without real-time system measurements. This paper presents a graph theory based centrality indices for vulnerability assessment of the power system due to various bus and branch contingencies using limited system information and provides a preliminary defense mechanism to prevent such an attack. Proposed work answers the fundamental question of possible attack scenarios by balancing risk (limited information with low risk to get caught or high risk attack to access more system information) and impact (identifying contingencies with maximal impact on system operation). Statistical comparisons are made between the graph theory measures compared to the corresponding DC power flow based N − X linear sensitivity measures. A unified N − X centrality based performance index is proposed and validated against the AC power flow based performance index by doing the real-time simulations of an N − 3 attack scenario. Defensive mechanisms using topology-based performance indices are also presented.