Modeling and assessing load redistribution attacks considering cyber vulnerabilities in power systems - Shi, Xingyu; Guo, Huan; Wang, Weiyu; Yin, Banghuang; Cao, Yijia (Frontiers in Energy Research, 2023)
As a typical type of false data injection attack (FDIA), load redistribution (LR) attacks have become one of the major cyber threats to power system operations, which falsifies load buses' measurements of substations. Existing LR attack methods find the attack vector, given that any substation is equally attackable. These methods contributed to the LR attack analysis in power systems. However, cyber vulnerabilities in communication links of substations are diverse, meaning the costs of falsifying load buses' measurements of substations are different. Therefore, how to quantitatively evaluate the costs and analyze the LR attack impact on power systems with the cost limits is full of practical significance. In the paper, the Bayesian attack graph model is employed to model the intruding process through cyber vulnerabilities, and the costs of falsifying load buses' measurements of substations are quantitatively evaluated by the Mean Time-To-Compromise (MTTC) model. Then, from the attacker's perspective, a bi-layer optimization model of LR attack considering MTTC together with limited attack resources and power flow constraint is proposed. Finally, the simulations on the IEEE 14-bus system demonstrate the impact of cyber vulnerabilities on LR attacks in power systems. Moreover, the attack scenario of the existing LR attack model is verified as a case of the proposed bi-level LR attack model with the sufficient attack time to intrude on all communication links.