Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems
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Date
2022Author
Mohammadpourfard, MostafaWeng, Yang
Khalili, Abdullah
Genç, İstemihan
Shefae, Alireza
Mohammadi-Ivatloo, Behnam
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M. Mohammadpourfard, Y. Weng, A. Khalili, I. Genc, A. Shefaei and B. Mohammadi-Ivatloo, "Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems," in IEEE Access, vol. 10, pp. 29277-29286, 2022, doi: 10.1109/ACCESS.2022.3151907.Abstract
The expansion of power systems over large geographical areas renders centralized processing inefficient. Therefore, the distributed operation is increasingly adopted. This work introduces a new type of attack against distributed state estimation of power systems, which operates on inter-area boundary buses. We show that the developed attack can circumvent existing robust state estimators and the convergence-based detection approaches. Afterward, we carefully design a deep learning-based cyber-anomaly detection mechanism to detect such attacks. Simulations conducted on the IEEE 14-bus system reveal that the developed framework can obtain a very high detection accuracy. Moreover, experimental results indicate that the proposed detector surpasses current machine learning-based detection methods.