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Proactive Security for the Industrial IoT Networks in the AI Era: A Framework for Continuous Threat Exposure Management

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  • Amith Ronad

Abstract

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.

Suggested Citation

  • Amith Ronad, 2025. "Proactive Security for the Industrial IoT Networks in the AI Era: A Framework for Continuous Threat Exposure Management," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 1576-1593, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:825
    DOI: 10.32628/CSEIT251112162
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112162
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