Cyber-physical attack conduction and detection in decentralized power systems

M Mohammadpourfard, Y Weng, A Khalili, I Genc… - IEEE …, 2022 - ieeexplore.ieee.org
M Mohammadpourfard, Y Weng, A Khalili, I Genc, A Shefaei, B Mohammadi-Ivatloo
IEEE Access, 2022ieeexplore.ieee.org
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 …
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.
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