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A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids

Author

Listed:
  • Meng Xia

    (Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Dajun Du

    (Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Minrui Fei

    (Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Xue Li

    (Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China)

  • Taicheng Yang

    (Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China)

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.

Suggested Citation

  • Meng Xia & Dajun Du & Minrui Fei & Xue Li & Taicheng Yang, 2020. "A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids," Energies, MDPI, vol. 13(11), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:11:p:2940-:d:368926
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    References listed on IDEAS

    as
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    4. Huixin Zhong & Dajun Du & Chuanjiang Li & Xue Li, 2018. "A Novel Sparse False Data Injection Attack Method in Smart Grids with Incomplete Power Network Information," Complexity, Hindawi, vol. 2018, pages 1-16, November.
    5. Mehdi Ganjkhani & Seyedeh Narjes Fallah & Sobhan Badakhshan & Shahaboddin Shamshirband & Kwok-wing Chau, 2019. "A Novel Detection Algorithm to Identify False Data Injection Attacks on Power System State Estimation," Energies, MDPI, vol. 12(11), pages 1-19, June.
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