LAPSE:2023.23560
Published Article

LAPSE:2023.23560
A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids
March 27, 2023
Abstract
To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible region and validity of the attack vector. For the above drawbacks, this paper has three main contributions: (1) To construct the appropriate attack evading bad data detection (BDD), the feasible region of the attack vector is proved by projection transformation theory. The acquisition of the feasible region can help the defender to formulate the defense strategy; (2) an effective attack is proposed and the constraint of effectiveness is obtained using norm theory; (3) the domain of the state variations caused by the attack vector in the feasible region is calculated, while the singular value decomposition method is adopted. Finally, an attack vector is constructed based on l 0 -norm using OMP algorithms in the feasible domain. Simulation results confirm the feasibility and effectiveness of the proposed technique.
To improve the security of smart grids (SGs) by finding the system vulnerability, this paper investigates the sparse attack vectors’ construction method for malicious false data injection attack (FDIA). The drawbacks of the existing attack vector construction methods include avoiding discussing the feasible region and validity of the attack vector. For the above drawbacks, this paper has three main contributions: (1) To construct the appropriate attack evading bad data detection (BDD), the feasible region of the attack vector is proved by projection transformation theory. The acquisition of the feasible region can help the defender to formulate the defense strategy; (2) an effective attack is proposed and the constraint of effectiveness is obtained using norm theory; (3) the domain of the state variations caused by the attack vector in the feasible region is calculated, while the singular value decomposition method is adopted. Finally, an attack vector is constructed based on l 0 -norm using OMP algorithms in the feasible domain. Simulation results confirm the feasibility and effectiveness of the proposed technique.
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Keywords
attack vector construction, effective attack, false data injection attack, smart grids, sparse attack
Subject
Suggested Citation
Xia M, Du D, Fei M, Li X, Yang T. A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids. (2023). LAPSE:2023.23560
Author Affiliations
Xia M: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Du D: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Fei M: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Li X: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Yang T: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Du D: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Fei M: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Li X: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Yang T: Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2940
Year
2020
Publication Date
2020-06-08
ISSN
1996-1073
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Original Submission
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PII: en13112940, Publication Type: Journal Article
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LAPSE:2023.23560
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https://doi.org/10.3390/en13112940
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Mar 27, 2023
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