APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE TO MITIGATE CYBERSECURITY CHALLENGES ON CRITICAL INFRASTRUCTURE PROJECTS: A LITERTURE REVIEW

Abstract Generative Artificial Intelligence (GenAI) refers to advanced machine learning techniques that autonomously generate data, text, and solutions across various applications, including cybersecurity. This technology has significant implications for enhancing security measures within critical infrastructure by leveraging its ability to analyze large datasets and identify anomalies indicative of cyber threats. The purpose of this study is to evaluate how GenAI would significantly enhance security of critical infrastructure project and its vital systems encompassing sectors such as energy, transportation, and communication that underpin national security and public safety. This study adopted a qualitative research approach rooted in utilisation of literature review approach, which aimed to critically review, interpret, and summarize the current state of knowledge on a specific subject on current and relevant academic, industry, business, and institutional literature resources via various databases, case studies, and government catalogue. Therefore, out of 102 initially selected and evaluated for this study, only 41 were found relevant and included for the study final evaluation and amalyses. The key findings reveal that generative artificial intelligence technology not only aids in threat detection but also plays a crucial role in developing proactive risk management strategies to mitigate the growing cybersecurity challenges facing critical infrastructure projects across various sectors. This study findings further indicated that the increasingly integration of GenAI into cybersecurity practices has been as a result of the rising sophistication of cyberattacks, which pose significant threats to critical infrastructure systems globally. Therefore, this study concluded and recommended that international strategic approach is urgently required as the global landscape of cyber threats continues to evolve, thus collaborative efforts among government, industry, and academia are essential to establish proactive frameworks that responsibly integrate GenAI into critical infrastructure while ensuring robust cybersecurity protocols.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-23
DOI
https://doi.org/10.5281/zenodo.18032090
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
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article

APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE TO MITIGATE CYBERSECURITY CHALLENGES ON CRITICAL INFRASTRUCTURE PROJECTS: A LITERTURE REVIEW

Iruka Chijindu Anugwo
Zenodo (CERN European Organization for Nuclear Research)
Organizational and Employee Performance
article

APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE TO MITIGATE CYBERSECURITY CHALLENGES ON CRITICAL INFRASTRUCTURE PROJECTS: A LITERTURE REVIEW

Iruka Chijindu Anugwo
article en

Abstract

Abstract Generative Artificial Intelligence (GenAI) refers to advanced machine learning techniques that autonomously generate data, text, and solutions across various applications, including cybersecurity. This technology has significant implications for enhancing security measures within critical infrastructure by leveraging its ability to analyze large datasets and identify anomalies indicative of cyber threats. The purpose of this study is to evaluate how GenAI would significantly enhance security of critical infrastructure project and its vital systems encompassing sectors such as energy, transportation, and communication that underpin national security and public safety. This study adopted a qualitative research approach rooted in utilisation of literature review approach, which aimed to critically review, interpret, and summarize the current state of knowledge on a specific subject on current and relevant academic, industry, business, and institutional literature resources via various databases, case studies, and government catalogue. Therefore, out of 102 initially selected and evaluated for this study, only 41 were found relevant and included for the study final evaluation and amalyses. The key findings reveal that generative artificial intelligence technology not only aids in threat detection but also plays a crucial role in developing proactive risk management strategies to mitigate the growing cybersecurity challenges facing critical infrastructure projects across various sectors. This study findings further indicated that the increasingly integration of GenAI into cybersecurity practices has been as a result of the rising sophistication of cyberattacks, which pose significant threats to critical infrastructure systems globally. Therefore, this study concluded and recommended that international strategic approach is urgently required as the global landscape of cyber threats continues to evolve, thus collaborative efforts among government, industry, and academia are essential to establish proactive frameworks that responsibly integrate GenAI into critical infrastructure while ensuring robust cybersecurity protocols.

Zenodo (CERN European Organization for Nuclear Research)
Durban University of Technology (ZA)
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Organizational and Employee Performance
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