Proactive Security for the Industrial IoT Networks in the AI Era: A Framework for Continuous Threat Exposure Management
DOI:
https://doi.org/10.32628/CSEIT251112162Keywords:
AI Security Integration, Continuous Threat Exposure Management, Industrial IoT Security, Proactive Security Framework, Real-time Threat DetectionAbstract
This article investigates the convergence of Industrial Internet of Things (IIoT) technologies and Artificial Intelligence (AI), exploring the evolving landscape of AI-powered attacks and the critical need for proactive security measures. To mitigate these risks, this paper proposes a multi-faceted security approach that combines traditional security techniques with AI-driven solutions. Focusing on Continuous Threat Exposure Management (CTEM) and Attack Surface Management (ASM), and emphasizing real-time threat detection, automated response mechanisms, and a robust human-AI collaboration model, the study explores a paradigm shift from reactive to proactive security measures in response to the evolving cyber threats facing modern industrial environments. Through an in-depth analysis of successful security implementations across diverse industrial sectors, this research demonstrates the efficacy of integrating AI-driven security measures with existing infrastructure. By proactively addressing these challenges, organizations can harness the power of AI to safeguard their digital assets and ensure the integrity of their operations.
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