Staying Ahead of Threats: A Review of AI and Cyber Security in Power Generation and Distribution

Author:

Mohamed Nachaat1,Oubelaid Adel2,Almazrouei Saif khameis3

Affiliation:

1. Rabdan Academy, (Homeland Security Department), Abu Dhabi, UAE

2. Laboratoire de Technologie Industrielle et de l’Information, Faculté de Technologie, Université de Bejaia, Bejaia 06000, Algeria

3. Ministry of Interior, (Smart Security Systems Department), UAE

Abstract

The integration of artificial intelligence (AI) and the Internet of Things (IoT) in the power generation and distribution industry presents opportunities and challenges, particularly in the area of cybersecurity. Previous studies have explored the potential of AI to enhance cybersecurity in power systems, but limitations in terms of sample size and scope have hindered a comprehensive understanding of the current state of the field. To address this gap, this paper presents a systematic literature review of 30 papers that analyzes and categorizes relevant research based on their focus on threats, solutions, and future trends. The results indicate that 30 articles provide evidence supporting the use of AI and machine learning techniques to significantly enhance cybersecurity in the power sector. However, the study also highlights the need for continuous monitoring, threat intelligence, and risk management to stay ahead of evolving threats. Notably, this paper provides novel insights into the use of cybersecurity measures, blockchain technology, and awareness of the impact of AI in the power sector, with 90% of organizations using cybersecurity measures, 50% employing blockchain technology, 20% experiencing a cyberattack, and 60% being aware of the impact of AI. The study's limitations include a lack of detailed information on the organizations studied, such as their size and location, and the absence of a standardized approach to data collection across the selected papers. Nonetheless, this paper offers a valuable contribution to the field of AI and cybersecurity in the power industry by providing a comprehensive overview of the current state of research and identifying key areas for further investigation.

Publisher

FOREX Publication

Subject

Electrical and Electronic Engineering,Engineering (miscellaneous)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3