LAUSR

This paper presents a systematic approach to explicitly quantify and evaluate the overloading associations among lines under load redistribution (LR) attacks. We define overloading associations as a measure of the statistical correlation between two sets of lines in terms of their susceptibility to simultaneous overloading. We then show how overloading associations can be obtained to capture the patterns of simultaneous line overloading potentially induced by malicious data manipulation and assess the network’s security risk in the face of the LR attack. Furthermore, we develop a novel priority line selection approach to identify key network components that are crucial for the system-level propagation of line overloading, based on which effective defensive insights can be obtained to protect the system from the severe damaging effects of LR attacks. The effectiveness of the proposed approach is validated on the IEEE 118-bus system. Simulation results show that the proposed approach is capable of revealing the properties of simultaneous line overloading in the network and supporting decision-making from both the attacker’s and the defender’s perspectives.