Alrowaili, Yazeed, Saxena, Neetesh ORCID: https://orcid.org/0000-0002-6437-0807 and Burnap, Peter ORCID: https://orcid.org/0000-0003-0396-633X 2024. Towards developing an asset-criticality identification framework in smart grids. Presented at: IEEE International Conference on Cyber Security and Resilience (CSR) Workshop on Security, Privacy and Resilience of Critical Assets in Critical Infrastructure (SPARC), London, UK, 2-4 Sept 2024. 2024 IEEE International Conference on Cyber Security and Resilience (CSR). IEEE, pp. 720-725. 10.1109/CSR61664.2024.10679477 |
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Abstract
Smart Grids combine advanced communication technologies with traditional power systems, enhancing performance and reliability but also introducing cyber and physical vulnerabilities. This paper presents a comprehensive framework to identify and prioritize key assets within these interconnected layers. The proposed framework employs graph-based integration to create nodes for cyber hosts and vulnerabilities, as well as power system components, assigning specific attributes to each. The framework establishes clear connections between cyber assets and power system elements by prioritizing cyber vulnerabilities through impact scores and graph metrics like closeness centrality and identifying key power components using electric degree and betweenness centrality. Scenario simulations are utilized to evaluate the impacts of disruptions across layers, revealing potential attack pathways and assessing associated risks. This integrated approach offers a detailed analysis of interconnected vulnerabilities, aiding in the development of targeted mitigation strategies to enhance the security of the overall smart grids.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | IEEE |
ISBN: | 979-8-3503-7536-7 |
Date of First Compliant Deposit: | 2 August 2024 |
Date of Acceptance: | 14 July 2024 |
Last Modified: | 07 Nov 2024 22:15 |
URI: | https://orca.cardiff.ac.uk/id/eprint/171133 |
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