Transforming Cybersecurity into Critical Energy Infrastructure: A Study on the Effectiveness of Artificial Intelligence

被引:2
|
作者
Govea, Jaime [1 ]
Gaibor-Naranjo, Walter [2 ]
Villegas-Ch, William [1 ]
机构
[1] Univ Las Amer, Escuela Ingn Cibersegur, Fac Ingn & Ciencias Aplicadas, Quito 170125, Ecuador
[2] Univ Politecn Salesiana, Carrera Ciencias Comp, Quito 170105, Ecuador
来源
SYSTEMS | 2024年 / 12卷 / 05期
关键词
artificial intelligence in cybersecurity; critical energy infrastructure; cyber threat detection; INDUSTRIAL CONTROL-SYSTEMS; SECURITY; TECHNOLOGY; AI;
D O I
10.3390/systems12050165
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
This work explores the integration and effectiveness of artificial intelligence in improving the security of critical energy infrastructure, highlighting its potential to transform cybersecurity practices in the sector. The ability of artificial intelligence solutions to detect and respond to cyber threats in critical energy infrastructure environments was evaluated through a methodology that combines empirical analysis and artificial intelligence modeling. The results indicate a significant increase in the threat detection rate, reaching 98%, and a reduction in incident response time by more than 70%, demonstrating the effectiveness of artificial intelligence in identifying and mitigating cyber risks quickly and accurately. In addition, implementing machine learning algorithms has allowed for the early prediction of failures and cyber-attacks, significantly improving proactivity and security management in energy infrastructure. This study highlights the importance of integrating artificial intelligence into energy infrastructure security strategies, proposing a paradigmatic change in cybersecurity management that increases operational efficiency and strengthens the resilience and sustainability of the energy sector against cyber threats.
引用
收藏
页数:26
相关论文
共 50 条
  • [1] Critical energy infrastructure and the evolution of cybersecurity
    Sanders, Peyton
    Bronk, Chris
    Bazilian, Morgan D.
    ELECTRICITY JOURNAL, 2022, 35 (10):
  • [2] Artificial Intelligence in Critical Infrastructure Systems
    Laplante, Phil
    Amaba, Ben
    COMPUTER, 2021, 54 (10) : 14 - 24
  • [3] Evaluating and Improving Cybersecurity Capabilities of the Energy Critical Infrastructure
    Curtis, Pamela D.
    Mehravari, Nader
    2015 IEEE INTERNATIONAL SYMPOSIUM ON TECHNOLOGIES FOR HOMELAND SECURITY (HST), 2015,
  • [4] Artificial intelligence in infrastructure construction: A critical review
    Chen, Ke
    Zhou, Xiaojie
    Bao, Zhikang
    Skibniewski, Miroslaw Jan
    Fang, Weili
    FRONTIERS OF ENGINEERING MANAGEMENT, 2025, 12 (01) : 24 - 38
  • [5] Cyber Threat Intelligence for Improving Cybersecurity and Risk Management in Critical Infrastructure
    Kure, Halima Ibrahim
    Islam, Shareeful
    JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2019, 25 (11) : 1478 - 1502
  • [6] Artificial Intelligence for Cybersecurity
    Ebert, Christof
    Beck, Maximilian
    IEEE SOFTWARE, 2023, 40 (06) : 27 - 34
  • [7] Artificial Intelligence in Cybersecurity: A Review and a Case Study
    Okdem, Selcuk
    Okdem, Sema
    APPLIED SCIENCES-BASEL, 2024, 14 (22):
  • [8] Artificial Intelligence & Cybersecurity: A Preliminary Study of Automated Pentesting with Offensive Artificial Intelligence
    Francois, Marin
    Arduin, Pierre-Emmanuel
    Merad, Myriam
    INFORMATION AND KNOWLEDGE SYSTEMS: DIGITAL TECHNOLOGIES, ARTIFICIAL INTELLIGENCE AND DECISION MAKING, ICIKS 2021, 2021, 425 : 131 - 138
  • [9] Protecting Critical Energy Infrastructure Through Intelligence
    Rudner, Martin
    INTERNATIONAL JOURNAL OF INTELLIGENCE AND COUNTERINTELLIGENCE, 2008, 21 (04) : 635 - 660
  • [10] Explainable Artificial Intelligence for Cybersecurity
    Sharma, Deepak Kumar
    Mishra, Jahanavi
    Singh, Aeshit
    Govil, Raghav
    Srivastava, Gautam
    Lin, Jerry Chun-Wei
    COMPUTERS & ELECTRICAL ENGINEERING, 2022, 103