Affiliation:
1. Cardiff University, Cathays, Cardiff, UK
2. University of California, Santa Cruz, CA
3. Georgia Institute of Technology, Atlanta, GA
Abstract
The smart grid (SG), regarded as the complex cyber-physical ecosystem of infrastructures, orchestrates advanced communication, computation, and control technologies to interact with the physical environment. Due to the high rewards that threats to the grid can realize, adversaries can mount complex cyber-attacks such as advanced persistent threats-based and coordinated attacks to cause operational malfunctions and power outages in the worst scenarios: The latter of which was reflected in the Ukrainian power grid attack. Despite widespread research on smart grid security, the impact of targeted attacks on control and power systems is anecdotal. This article reviews the smart grid security from collaborative factors, emphasizing the situational awareness (SA). Specifically, we propose a threat modeling framework and review the nature of cyber-physical attacks to understand their characteristics and impacts on the smart grid’s control and physical systems. We examine the existing threats detection and defense capabilities, such as intrusion detection systems (IDSs), moving target defense (MTD), and co-simulation techniques, along with discussing the impact of attacks through situational awareness and power system metrics. We discuss the human factor aspects for power system operators in analyzing the impacts of cyber-attacks. Finally, we investigate the research challenges with key research gaps to shed light on future research directions.
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Reference130 articles.
1. Sridhar Adepu, Nandha Kumar Kandasamy, and Aditya Mathur. 2018. Epic: An electric power testbed for research and training in cyber physical systems security. In Proceedings of the Computer Security. Springer, 37–52.
2. Challenges and performance metrics for security operations center analysts: a systematic review
3. Enoch Agyepong, Yulia Cherdantseva, Philipp Reinecke, and Pete Burnap. 2020. Towards a framework for measuring the performance of a security operations center analyst. In Proceedings of the 2020 International Conference on Cyber Security and Protection of Digital Services. IEEE, 1–8.
4. Unsupervised Machine Learning-Based Detection of Covert Data Integrity Assault in Smart Grid Networks Utilizing Isolation Forest
5. A Survey on Cyber Situation-awareness Systems: Framework, Techniques, and Insights
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