Abstract
The increasing adoption of Industrial Internet of Things (IIoT) systems in critical sectors has enhanced operational efficiency but also exposed these systems to sophisticated cyber threats. This paper examines the current landscape of cyber-physical security in industrial environments, highlighting the limitations of traditional frameworks and the emerging role of artificial intelligence (AI) in addressing these challenges. A proposed AI-powered cybersecurity framework is introduced, emphasizing its modular architecture, real-time threat detection capabilities, and seamless integration with existing protocols. The framework addresses gaps in current practices, such as the lack of proactive measures, challenges with legacy systems, and data scarcity, while enhancing system resilience and reliability. The study also explores the potential impact of AI-driven solutions on industrial cybersecurity and provides recommendations for research, policy, and industrial adoption. By fostering innovation and collaboration, this work aims to position AI as a cornerstone in safeguarding critical industrial systems against evolving cyber threats.
Published Version
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