| Title |
The Role of Machine Learning Algorithms in Smart Grid Cybersecurity. |
| ID_Doc |
61962 |
| Authors |
Diaba, SY |
| Title |
The Role of Machine Learning Algorithms in Smart Grid Cybersecurity. |
| Year |
2024 |
| Published |
|
| DOI |
10.1109/AIE61866.2024.10561386 |
| 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 cybersecurity 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. |
| Author Keywords |
Artificial intelligence; cyberattacks; cybersecurity; machine learning; smart grid |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001265777700015 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Energy & Fuels; Telecommunications |
| Research Area |
Computer Science; Energy & Fuels; Telecommunications |
| PDF |
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