International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 3
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AI-Enhanced Zero Trust Architectures for Critical Infrastructure Security: An Extensive Framework for Advanced Cybersecurity

Author(s) Mr. Harshit Chauhan, Prof. Wajahat Gh Mohd, Tarun Kumar
Country India
Abstract In today's digitally connected world, critical infrastructure systems face significant cybersecurity concerns. Traditional perimeter-based security solutions have proven ineffective against sophisticated cyber attacks on critical infrastructure such as power grids, water treatment facilities, transportation networks, and telecommunications systems. This study provides a comprehensive review of AI-powered Zero Trust Architectures (ZTA) as a disruptive method to protect critical infrastructure. Our analysis of current implementations, new technologies, and strategic frameworks shows that incorporating artificial intelligence strengthens the Zero Trust principles of "never trust, always verify" to develop adaptive and intelligent security ecosystems. Our research focuses on AI-driven security automation, machine learning-based threat detection, and zero trust network access controls designed for critical infrastructure. AI-powered ZTA systems can reduce security incident response times by up to 85% and improve threat detection accuracy to 99.2% in controlled scenarios. This study adds to the understanding of cybersecurity resilience by offering practical insights for infrastructure operators, regulators, and security professionals negotiating the convergence of AI and zero trust security paradigms.
Keywords Artificial Intelligence, Critical infrastructure, Incident response, Network access controls, Perimeter-based security, Security automation, Zero Trust Architecture
Field Computer Applications
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-06-02
DOI https://doi.org/10.36948/ijfmr.2026.v08i03.80239
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E-ISSN 2582-2160
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