AI AND PERFORMANCE CAPABILITIES OF CYBERSECURITY IN THE ENERGY INDUSTRY

Abstract: The energy industry is significant by digitalization, renewable integration, and automation, making it increasingly reliant on interconnected systems. This evolution exposes the sector to sophisticated cyber threats targeting critical infrastructure, operational technologies (OT), and supply chains, enhancing the cybersecurity landscape of the energy industry, offering several opportunities in the industry. This article explores dual role of AI in shaping the energy industry's cybersecurity framework, emphasizing its impact on threat prevention and performance optimization. Key aspects such as the integration of AI-driven anomaly detection systems, real-time response capabilities, and secure energy grid operations are analyzed. The article also examines the challenges of implementing AI-based cybersecurity, including ethical concerns, data privacy, and the risk of adversarial AI attacks. The article shows the necessity for a fair approach to harness AI’s potential while ensuring robust, secure, and efficient energy operations.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-23
DOI
https://doi.org/10.5281/zenodo.14550466
Primary Topic
Internet of Things and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

AI AND PERFORMANCE CAPABILITIES OF CYBERSECURITY IN THE ENERGY INDUSTRY

Zenodo (CERN European Organization for Nuclear Research)
Internet of Things and AI
article

AI AND PERFORMANCE CAPABILITIES OF CYBERSECURITY IN THE ENERGY INDUSTRY

article en

Abstract

Abstract: The energy industry is significant by digitalization, renewable integration, and automation, making it increasingly reliant on interconnected systems. This evolution exposes the sector to sophisticated cyber threats targeting critical infrastructure, operational technologies (OT), and supply chains, enhancing the cybersecurity landscape of the energy industry, offering several opportunities in the industry. This article explores dual role of AI in shaping the energy industry's cybersecurity framework, emphasizing its impact on threat prevention and performance optimization. Key aspects such as the integration of AI-driven anomaly detection systems, real-time response capabilities, and secure energy grid operations are analyzed. The article also examines the challenges of implementing AI-based cybersecurity, including ethical concerns, data privacy, and the risk of adversarial AI attacks. The article shows the necessity for a fair approach to harness AI’s potential while ensuring robust, secure, and efficient energy operations.

Zenodo (CERN European Organization for Nuclear Research)
University of Port Harcourt (NG), Rivers State University (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Internet of Things and AI
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AI AND PERFORMANCE CAPABILITIES OF CYBERSECURITY IN THE ENERGY INDUSTRY · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS