LAPSE:2023.9827
Published Article
LAPSE:2023.9827
Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions
Jianguo Ding, Attia Qammar, Zhimin Zhang, Ahmad Karim, Huansheng Ning
February 27, 2023
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.
Keywords
Artificial Intelligence, blockchain, cyberattacks, cybersecurity, smart grids, vulnerabilities
Suggested Citation
Ding J, Qammar A, Zhang Z, Karim A, Ning H. Cyber Threats to Smart Grids: Review, Taxonomy, Potential Solutions, and Future Directions. (2023). LAPSE:2023.9827
Author Affiliations
Ding J: Department of Computer Science, Blekinge Institute of Technology, 37179 Karlskrona, Sweden [ORCID]
Qammar A: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
Zhang Z: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China [ORCID]
Karim A: Department of Information Technology, Bahauddin Zakariya University, Multan 60000, Pakistan
Ning H: School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China [ORCID]
Journal Name
Energies
Volume
15
Issue
18
First Page
6799
Year
2022
Publication Date
2022-09-17
Published Version
ISSN
1996-1073
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PII: en15186799, Publication Type: Journal Article
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LAPSE:2023.9827
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doi:10.3390/en15186799
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