Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems

Journal Article (2022)
Author(s)

Mostafa Mohammadpourfard (Sahand University of Technology, Istanbul Technical University)

Yang Weng (Arizona State University)

Abdullah Khalili (University of Hormozgan)

Istemihan Genc (Istanbul Technical University)

Alireza Shefaei (University of Tabriz, TU Delft - Civil Engineering & Geosciences)

Behnam Mohammadi-Ivatloo (Muğla Sıtkı Koçman University, University of Tabriz)

Research Group
Water Resources
DOI related publication
https://doi.org/10.1109/ACCESS.2022.3151907 Final published version
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Publication Year
2022
Language
English
Research Group
Water Resources
Journal title
IEEE Access
Volume number
10
Pages (from-to)
29277-29286
Downloads counter
363
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Institutional Repository
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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.