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Cyber Risks to Critical Smart Grid Assets of Industrial Control Systems

Author

Listed:
  • Chenyang Liu

    (School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK)

  • Yazeed Alrowaili

    (School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK)

  • Neetesh Saxena

    (School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3AT, UK)

  • Charalambos Konstantinou

    (CEMSE Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia)

Abstract

Cybersecurity threats targeting industrial control systems (ICS) have significantly increased in the past years. Moreover, the need for users/operators to understand the consequences of attacks targeting these systems and protect all assets is vital. This work explores asset discovery in ICS and how to rank these assets based on their criticality. This paper also discusses asset discovery and its components. We further present existing solutions and tools for asset discovery. We implement a method to identify critical assets based on their connection and discuss related results and evaluation. The evaluation utilises four attack scenarios to stress the importance of protecting these critical assets since the failure to protect them can lead to serious consequences. Using a 12-bus system case, our results show that targeting such a system can increase and overload transmission lines values to 120% and 181% MVA, which can affect the power supply and disrupt service, and it can increase the cost up to 60%, affecting the productivity of this electric grid.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5501-:d:628428
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    Citations

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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. Aiman J. Albarakati & Mohamed Azeroual & Younes Boujoudar & Lahcen EL Iysaouy & Ayman Aljarbouh & Asifa Tassaddiq & Hassane EL Markhi, 2022. "Multi-Agent-Based Fault Location and Cyber-Attack Detection in Distribution System," Energies, MDPI, vol. 16(1), pages 1-16, December.
    3. Seppo Borenius & Pavithra Gopalakrishnan & Lina Bertling Tjernberg & Raimo Kantola, 2022. "Expert-Guided Security Risk Assessment of Evolving Power Grids," Energies, MDPI, vol. 15(9), pages 1-25, April.
    4. Olga Zhironkina & Sergey Zhironkin, 2023. "Technological and Intellectual Transition to Mining 4.0: A Review," Energies, MDPI, vol. 16(3), pages 1-37, February.

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