The Role of Machine Learning Algorithms in Smart Grid Cybersecurity

Sayawu Yakubu Diaba (Corresponding author)

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

In the rapidly evolving landscape of smart grid cybersecurity, the integration of artificial intelligence and machine learning algorithms has emerged as a pivotal element in fortifying infrastructures against sophisticated cyberattacks. This paper investigates the transformative role of artificial intelligence and machine learning in enhancing the security of smart grids, which are increasingly becoming targets for high risk cyberattacks. By contextualizing the significance of cyber-security within the energy sector, and by elucidating the fundamental principles of artificial intelligence and machine learning algorithms. An in-depth exploration of how these algorithms is revolutionizing cyberattack detection, predictive analytics, and automated response strategies in the smart grid domain are evaluated. Utilizing state-of-the-art data, this paper presents a comprehensive analysis of some leading machine learning algorithm responses, highlighting key trends and emerging patterns.

Original languageEnglish
Title of host publication2024 International Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024
PublisherIEEE Institute of Electrical and Electronic Engineers
Number of pages7
ISBN (Electronic)979-8-3503-6496-5
ISBN (Print)979-8-3503-6497-2
DOIs
Publication statusPublished - 2024
MoE publication typeA4 Article in a conference publication
EventInternational Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024 - Vaasa, Finland
Duration: 20 May 202422 May 2024

Conference

ConferenceInternational Workshop on Artificial Intelligence and Machine Learning for Energy Transformation, AIE 2024
Country/TerritoryFinland
CityVaasa
Period20/05/2422/05/24

Keywords

  • Artificial intelligence
  • cyber-security
  • cyberattacks
  • machine learning
  • smart grid

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