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Open AccessArticle

A Novel Detection Algorithm to Identify False Data Injection Attacks on Power System State Estimation

1
Department of Electrical Engineering, Sharif University of Technology, Tehran P.O. Box 11365-11155, Iran
2
Independent Researcher, Sari 4816783787, Iran
3
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
4
Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam
5
Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(11), 2209; https://doi.org/10.3390/en12112209
Received: 21 February 2019 / Revised: 27 March 2019 / Accepted: 4 April 2019 / Published: 10 June 2019
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Abstract

This paper provides a novel bad data detection processor to identify false data injection attacks (FDIAs) on the power system state estimation. The attackers are able to alter the result of the state estimation virtually intending to change the result of the state estimation without being detected by the bad data processors. However, using a specific configuration of an artificial neural network (ANN), named nonlinear autoregressive exogenous (NARX), can help to identify the injected bad data in state estimation. Considering the high correlation between power system measurements as well as state variables, the proposed neural network-based approach is feasible to detect any potential FDIAs. Two different strategies of FDIAs have been simulated in power system state estimation using IEEE standard 14-bus test system for evaluating the performance of the proposed method. The results indicate that the proposed bad data detection processor is able to detect the false injected data launched into the system accurately. View Full-Text
Keywords: state estimation; false data injection attack (FDIA); artificial neural network (ANN); nonlinear autoregressive exogenous (NARX) bad data detection state estimation; false data injection attack (FDIA); artificial neural network (ANN); nonlinear autoregressive exogenous (NARX) bad data detection
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Ganjkhani, M.; Fallah, S.N.; Badakhshan, S.; Shamshirband, S.; Chau, K.-W. A Novel Detection Algorithm to Identify False Data Injection Attacks on Power System State Estimation. Energies 2019, 12, 2209.

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