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Enhancing Cybersecurity in Smart Grids: False Data Injection and Its Mitigation

Author

Listed:
  • Derya Betul Unsal

    (Department of Energy Science and Technology, Renewable Energy Research Center, Cumhuriyet University, Sivas 58140, Turkey)

  • Taha Selim Ustun

    (Fukushima Renewable Energy Institute, AIST (FREA), Koriyama 963-0298, Japan)

  • S. M. Suhail Hussain

    (Fukushima Renewable Energy Institute, AIST (FREA), Koriyama 963-0298, Japan)

  • Ahmet Onen

    (Department of Electrical and Electronics Engineering, Abdullah Gul University, Kayseri 38170, Turkey)

Abstract

Integration of information technologies with power systems has unlocked unprecedented opportunities in optimization and control fields. Increased data collection and monitoring enable control systems to have a better understanding of the pseudo-real-time condition of power systems. In this fashion, more accurate and effective decisions can be made. This is the key towards mitigating negative impacts of novel technologies such as renewables and electric vehicles and increasing their share in the overall generation portfolio. However, such extensive information exchange has created cybersecurity vulnerabilities in power systems that were not encountered before. It is imperative that these vulnerabilities are understood well, and proper mitigation techniques are implemented. This paper presents an extensive study of cybersecurity concerns in Smart grids in line with latest developments. Relevant standardization and mitigation efforts are discussed in detail and then the classification of different cyber-attacks in smart grid domain with special focus on false data injection (FDI) attack, due to its high impact on different operations. Different uses of this attack as well as developed detection models and methods are analysed. Finally, impacts on smart grid operation and current challenges are presented for future research directions.

Suggested Citation

  • Derya Betul Unsal & Taha Selim Ustun & S. M. Suhail Hussain & Ahmet Onen, 2021. "Enhancing Cybersecurity in Smart Grids: False Data Injection and Its Mitigation," Energies, MDPI, vol. 14(9), pages 1-36, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2657-:d:549412
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    References listed on IDEAS

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    Cited by:

    1. Ren Liu & Hussain M. Mustafa & Zhijie Nie & Anurag K. Srivastava, 2022. "Reachability-Based False Data Injection Attacks and Defence Mechanisms for Cyberpower System," Energies, MDPI, vol. 15(5), pages 1-18, February.
    2. Nakkeeran Murugesan & Anantha Narayanan Velu & Bagavathi Sivakumar Palaniappan & Balamurugan Sukumar & Md. Jahangir Hossain, 2024. "Mitigating Missing Rate and Early Cyberattack Discrimination Using Optimal Statistical Approach with Machine Learning Techniques in a Smart Grid," Energies, MDPI, vol. 17(8), pages 1-34, April.
    3. Taha Selim Ustun, 2022. "Cybersecurity in Smart Grids," Energies, MDPI, vol. 15(15), pages 1-3, July.

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