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Security Fortifying Critical Infrastructure: AI-Based Identity and Access Management (IAM) for Industrial Automation
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Author(s): Sandhya Samant (COER University, India), Pawan Kumar Goel (Raj Kumar Goel Institute of Technology, Ghaziabad, India), Himanshu Tyagi (Quantum University, India)and Aafia Hussain (College of Engineering, Roorkee, India)
Copyright: 2025
Pages: 32
Source title:
AI-Enhanced Cybersecurity for Industrial Automation
Source Author(s)/Editor(s): Hari Mohan Pandey (Bournemouth University, UK)and Pawan Kumar Goel (Raj Kumar Goel Institute of Technology, India)
DOI: 10.4018/979-8-3373-3241-3.ch021
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Abstract
Industrial automation has created a new era of connected systems, making strong security essential. Traditional Identity and Access Management (IAM) systems, though once effective, now struggle with the evolving demands of complex industrial environments. Static IAM approaches fall short as networks expand, highlighting the need for intelligent, adaptive solutions. AI introduces dynamic, context-aware security through technologies like machine learning, deep learning, behavioral biometrics, and anomaly detection. These enable continuous authentication, real-time access control, and improved identity verification. This work explores AI-driven IAM in sectors such as manufacturing and energy, outlining benefits like enhanced threat detection, compliance, operational resilience, and faster response. Challenges include data protection, legacy system integration, and scalability. Future directions include blockchain-based identity, Federated Learning, Explainable AI, and insider threat detection—ensuring AI-powered IAM evolves to meet the future of industrial cybersecurity.
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