Sani, Abubakar Sadiq, Yuan, Dong, Lawal, Yahaya, Loukas, George ORCID: https://orcid.org/0000-0003-3559-5182 and Dong, Zhao Yang (2024) A sustainable dispositional and situational security awareness model for Smart Grids. In: IEEE Global Energy Conference 2024. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey. (In Press)

PDF (Author's Accepted Manuscript) 48882 SANI_A_Sustainable_Dispositional_And_Situational_Security_Awareness_Model_For_Smart_Grids_(AAM)_2024.pdf - Accepted Version Restricted to Repository staff only Download (401kB) | Request a copy

Abstract

The continuous introduction of emerging technologies such as Artificial Intelligence (AI) in smart grids has improved the reliability of operations and communication among components in the grids. However, such technologies can become unsustainable and further introduce security vulnerabilities. Any potential impact of security attacks on a smart grid component such as a sensor, either through internal or external adversaries, may lead to a breakdown of operations in the grids. Additionally, the large number of components along with their dependencies on emerging technologies may hinder the ability of grid operators to sustainably identify security flaws. Note that sustainability (of smart grid security) in this work refers to the ability to mitigate security vulnerabilities or attacks without overdependence on grid operators or emerging technologies that introduce high computational overheads. In this paper, we propose a sustainable dispositional and situational security awareness model through the utilization of a Fuzzy Cognitive Map (FCM) to effectively reveal and mitigate security vulnerabilities in the smart grids without overdependence on emerging technologies. We conducted some case studies on a Supervisory Control and Data Acquisition (SCADA) system to show the usefulness of our model.

Item Type:	Conference Proceedings
Title of Proceedings:	IEEE Global Energy Conference 2024
Uncontrolled Keywords:	Smart Grids, sustainability, dispositional and situational security awareness, fuzzy cognitive map, security
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	16 Dec 2024 11:18
URI:	http://gala.gre.ac.uk/id/eprint/48882

Actions (login required)

View Item

Downloads