Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems

Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems

Mohammadpourfard, Mostafa (Istanbul Technical University; Sahand University of Technology)
Weng, Yang (Arizona State University)
Khalili, Abdullah (University of Hormozgan)
Genc, Istemihan (Istanbul Technical University)
Shefaei, A. (TU Delft Water Resources; University of Tabriz)
Mohammadi-Ivatloo, Behnam (University of Tabriz; Muğla Sıtkı Koçman University)

2022

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.

cyber-attacks
Deep learning
distributed state estimation
smart grids

http://resolver.tudelft.nl/uuid:db9e8d89-b477-487e-82dd-1cce46125e7a

https://doi.org/10.1109/ACCESS.2022.3151907

2169-3536

IEEE Access, 10, 29277-29286

Institutional Repository

journal article

© 2022 Mostafa Mohammadpourfard, Yang Weng, Abdullah Khalili, Istemihan Genc, A. Shefaei, Behnam Mohammadi-Ivatloo