AI-Driven Cybersecurity for Industrial Automation: Resilient Solutions for Industry 4.0

Manoj Govindaraj Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, India https://orcid.org/0000-0003-2830-7875 Anitha Kumari P. Vels Institute of Science, Technology, and Advanced Studies, India P. Shakila St. Joseph's University, Bangalore, India Jenifer Lawrence Woldia University, Ethiopia https://orcid.org/0000-0002-4115-1521 AI-Driven Cybersecurity for Industrial Automation Resilient Solutions for Industry 4.0

The rise of Industry 4.0 has transformed traditional industrial environments through the integration of smart technologies, IoT devices, and interconnected systems. While these innovations improve efficiency and productivity, they also expose critical infrastructure to sophisticated cyber threats. This paper explores the application of Artificial Intelligence (AI) in enhancing cybersecurity for industrial automation systems. It examines how AI-driven solutions such as machine learning, deep learning, and behavior analytics can detect anomalies, predict attacks, and automate threat responses in real-time. The study also highlights challenges in adopting AI, including data privacy, system complexity, and the need for resilient and explainable models. By analyzing current use cases and emerging trends, the paper proposes a framework for developing adaptive, resilient, and intelligent cybersecurity systems tailored to the unique demands of Industry 4.0.
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