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Comprehensive survey and taxonomies of false data injection attacks in smart grids: attack models, targets, and impacts

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  • Reda, Haftu Tasew
  • Anwar, Adnan
  • Mahmood, Abdun

Abstract

Smart Grid is organically growing over the centrally controlled power system and becoming a massively interconnected cyber–physical system with advanced technologies of fast communication and intelligence (such as Internet of Things, smart meters, and intelligent electronic devices). While the convergence of a significant number of cyber–physical elements has enabled the Smart Grid to be far more efficient and competitive in addressing the growing global energy challenges, it has also introduced a large number of vulnerabilities in the cyber–physical space culminating in violations of data availability, integrity, and confidentiality. Recently, false data injection (FDI) has become one of the most critical types of cyberattacks, and appears to be a focal point of interest for both research and industry. To this end, this paper presents a comprehensive review in the recent advances of the FDI attacks, with particular emphasis on adversarial models, attack targets, and impacts on the Smart Grid infrastructure. This review paper aims to provide a thorough understanding of the incumbent threats affecting the entire spectrum of the Smart Grid. Related literature are analyzed and compared in terms of their theoretical and practical implications to the Smart Grid cybersecurity. In conclusion, a vast range of technical limitations of existing false data attack research is identified, and a number of future research directions is recommended.

Suggested Citation

  • Reda, Haftu Tasew & Anwar, Adnan & Mahmood, Abdun, 2022. "Comprehensive survey and taxonomies of false data injection attacks in smart grids: attack models, targets, and impacts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    • Handle: RePEc:eee:rensus:v:163:y:2022:i:c:s1364032122003306
    DOI: 10.1016/j.rser.2022.112423
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    References listed on IDEAS

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    1. Shepard, Daniel P. & Humphreys, Todd E. & Fansler, Aaron A., 2012. "Evaluation of the vulnerability of phasor measurement units to GPS spoofing attacks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 5(3), pages 146-153.
    2. Dai Wang & Xiaohong Guan & Ting Liu & Yun Gu & Chao Shen & Zhanbo Xu, 2014. "Extended Distributed State Estimation: A Detection Method against Tolerable False Data Injection Attacks in Smart Grids," Energies, MDPI, vol. 7(3), pages 1-22, March.
    3. Kabalci, Yasin, 2016. "A survey on smart metering and smart grid communication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 302-318.
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    Cited by:

    1. Erdal Irmak & Ersan Kabalci & Yasin Kabalci, 2023. "Digital Transformation of Microgrids: A Review of Design, Operation, Optimization, and Cybersecurity," Energies, MDPI, vol. 16(12), pages 1-58, June.

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