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Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions

Author

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  • Jianguo Ding

    (Department of Computer Science, Blekinge Institute of Technology, 37179 Karlskrona, Sweden)

  • Attia Qammar

    (School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Zhimin Zhang

    (School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Ahmad Karim

    (Department of Information Technology, Bahauddin Zakariya University, Multan 60000, Pakistan)

  • Huansheng Ning

    (School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

Smart Grids (SGs) are governed by advanced computing, control technologies, and networking infrastructure. However, compromised cybersecurity of the smart grid not only affects the security of existing energy systems but also directly impacts national security. The increasing number of cyberattacks against the smart grid urgently necessitates more robust security protection technologies to maintain the security of the grid system and its operations. The purpose of this review paper is to provide a thorough understanding of the incumbent cyberattacks’ influence on the entire smart grid ecosystem. In this paper, we review the various threats in the smart grid, which have two core domains: the intrinsic vulnerability of the system and the external cyberattacks. Similarly, we analyze the vulnerabilities of all components of the smart grid (hardware, software, and data communication), data management, services and applications, running environment, and evolving and complex smart grids. A structured smart grid architecture and global smart grid cyberattacks with their impact from 2010 to July 2022 are presented. Then, we investigated the the thematic taxonomy of cyberattacks on smart grids to highlight the attack strategies, consequences, and related studies analyzed. In addition, potential cybersecurity solutions to smart grids are explained in the context of the implementation of blockchain and Artificial Intelligence (AI) techniques. Finally, technical future directions based on the analysis are provided against cyberattacks on SGs.

Suggested Citation

  • Jianguo Ding & Attia Qammar & Zhimin Zhang & Ahmad Karim & Huansheng Ning, 2022. "Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions," Energies, MDPI, vol. 15(18), pages 1-37, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6799-:d:917417
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    Cited by:

    1. Szymon Stryczek & Marek Natkaniec, 2022. "Internet Threat Detection in Smart Grids Based on Network Traffic Analysis Using LSTM, IF, and SVM," Energies, MDPI, vol. 16(1), pages 1-23, December.
    2. Mikołaj Gwiazdowicz & Marek Natkaniec, 2023. "Feature Selection and Model Evaluation for Threat Detection in Smart Grids," Energies, MDPI, vol. 16(12), pages 1-25, June.
    3. Smitha Joyce Pinto & Pierluigi Siano & Mimmo Parente, 2023. "Review of Cybersecurity Analysis in Smart Distribution Systems and Future Directions for Using Unsupervised Learning Methods for Cyber Detection," Energies, MDPI, vol. 16(4), pages 1-24, February.
    4. 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.
    5. Wenbing Zhao & Quan Qi & Jiong Zhou & Xiong Luo, 2023. "Blockchain-Based Applications for Smart Grids: An Umbrella Review," Energies, MDPI, vol. 16(17), pages 1-35, August.
    6. Tehseen Mazhar & Hafiz Muhammad Irfan & Sunawar Khan & Inayatul Haq & Inam Ullah & Muhammad Iqbal & Habib Hamam, 2023. "Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods," Future Internet, MDPI, vol. 15(2), pages 1-37, February.
    7. Amitkumar V. Jha & Bhargav Appasani & Deepak Kumar Gupta & Bharati S. Ainapure & Nicu Bizon, 2023. "A Blockchain-Enabled Approach for Enhancing Synchrophasor Measurement in Smart Grid 3.0," Sustainability, MDPI, vol. 15(19), pages 1-20, October.

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