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Detection of False Data Injection Attacks in Distributed State Estimation of Power Networks
Title: | Detection of False Data Injection Attacks in Distributed State Estimation of Power Networks |
Authors: | Obata, Sho Browse this author | Kobayashi, Koichi Browse this author →KAKEN DB | Yamashita, Yuh Browse this author →KAKEN DB |
Keywords: | power networks | distributed state estimation | false data injection attacks | ADMM (Alternating Direction Method of Multipliers) |
Issue Date: | 1-May-2023 |
Publisher: | IEICE - Institute of the Electronics, Information and Communication Engineers |
Journal Title: | IEICE transactions on fundamentals of electronics communications and computer sciences |
Volume: | E106A |
Issue: | 5 |
Start Page: | 729 |
End Page: | 735 |
Publisher DOI: | 10.1587/transfun.2022MAP0010 |
Abstract: | In a power network, it is important to detect a cyber attack. In this paper, we propose a method for detecting false data injection (FDI) attacks in distributed state estimation. An FDI attack is well known as one of the typical cyber attacks in a power network. As a method of FDI attack detection, we consider calculating the residual (i.e., the difference between the observed and estimated values). In the proposed detection method, the tentative residual (estimated error) in ADMM (Alternating Direction Method of Multipliers), which is one of the powerful methods in distributed optimization, is applied. First, the effect of an FDI attack is analyzed. Next, based on the analysis result, a detection parameter is introduced based on the residual. A detection method using this parameter is then proposed. Finally, the proposed method is demonstrated through a numerical example on the IEEE 14-bus system. |
Rights: | copyright©2023 IEICE |
Type: | article |
URI: | http://hdl.handle.net/2115/90179 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 小林 孝一
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