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Reachability-Based False Data Injection Attacks and Defence Mechanisms for Cyberpower System

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  • Ren Liu

    (State Key Laboratory of HVDC, National Energy Power Grid Technology R&D Centre, Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System, CSG Key Laboratory for Power System Simulation, Electric Power Research Institute, China Southern Power Grid, Guangzhou 510663, China)

  • Hussain M. Mustafa

    (Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA)

  • Zhijie Nie

    (GE Digital, Bothell, WA 98011, USA)

  • Anurag K. Srivastava

    (Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA)

Abstract

With the push for higher efficiency and reliability, an increasing number of intelligent electronic devices (IEDs) and associated information and communication technology (ICT) are integrated into the Internet of Things (IoT)-enabled smart grid. These advanced technologies and IEDs also bring potential vulnerabilities to the intelligent cyber–physical smart grid. State estimation, as a primary step of system monitoring and situational awareness, is a potential target for attackers. A number of other smart grid applications, such as voltage stability assessment and contingency screening, utilize state estimation results as input data. False data injection (FDI) is a specific way to attack state estimation by manipulating input data. Existing research mainly focuses on the mathematical analysis of FDI attacks; however, in these methods, discussions of reachability requirements to compromise measurements considering cyberinfrastructure are limited. Reachability is defined as a measure that estimates the number of hosts to compromise for the possible FDI. Most of the existing FDI attack methods require the simultaneous manipulation on multiple measurement devices in different substations, in order to bypass the bad data detection, which may be impractical. In this paper, a new type of reachability-based FDI attack considering the cybernetwork with a practical attack is proposed and validated on two IEEE test systems. The corresponding defence mechanisms are (a) decentralized state estimation (DSE), (b) DSE with additional backup computational nodes, (c) communication network rerouting, and (d) intrusion detection system, and they were developed and presented with validation for two IEEE test systems with superior performance for an IoT-enabled intelligent smart grid system.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1754-:d:759672
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    References listed on IDEAS

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    1. Chenyang Liu & Yazeed Alrowaili & Neetesh Saxena & Charalambos Konstantinou, 2021. "Cyber Risks to Critical Smart Grid Assets of Industrial Control Systems," Energies, MDPI, vol. 14(17), pages 1-19, September.
    2. Liang Ma & Gang Xu, 2020. "Distributed Resilient Voltage and Reactive Power Control for Islanded Microgrids under False Data Injection Attacks," Energies, MDPI, vol. 13(15), pages 1-27, July.
    3. 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.
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    Cited by:

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