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<p>The intersection of smart home Internet of Things (IoT) devices, enterprise Information Technology (IT) infrastructures and Operational Technology (OT) systems has greatly expanded the cyberattack surface, opening up smart environments to advanced persistent threats (APTs), ransomware, insider attacks and OT protocol exploits. Current cyber security solutions are largely domain specific, and do not have a unified approach for cross domain threat correlation, adaptive response orchestration and proactive cyber resilience. In this regard, this study introduces a novel framework called Cross-Domain Cyber Resilience Framework (CD-CRF) that combines multi-domain telemetry fusion, behavioral anomaly detection, intelligent threat deduction, probabilistic risk scoring, and adaptive response orchestration under a single architecture. The framework utilizes signature independent behavioral analytics and cross domain threat correlation with identification of complex multi-stage attacks in heterogeneous Home, IT and OT environments. Experimental assessment was performed with a set of heterogenous cybersecurity data sets, including intrusion detection logs, traces of ransomware activities, IoT botnet traffic, SCADA/ICS telemetry, authentication data and communication data for malware. The proposed CD-CRF successfully reduced the false positive rate to 1.8%, and attained a detection accuracy of 98.6%, threat prediction rate of 94.8% and a cross-domain correlation efficiency of 97.1%. Moreover, it had a response time of 120ms, about 50% faster mitigation than traditional methods, and statistically significantly outperformed GCSM and CAT and TinyML models (<i>p</i> &lt; 0.05). The results show that CD-CRF improves cyber situational awareness, it increases the ability to detect threats early, it decreases operational risks, and it offers scalable, adaptive cyber resilience solution to converged IT–OT environments.</p>

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Cyber resilience across domains: an in-depth exploration of cybersecurity practices and paradigms from the home environment to Operational Technology (OT)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月26日

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  • T. Sakthivel,
  • K. Balasubramanian

摘要

The intersection of smart home Internet of Things (IoT) devices, enterprise Information Technology (IT) infrastructures and Operational Technology (OT) systems has greatly expanded the cyberattack surface, opening up smart environments to advanced persistent threats (APTs), ransomware, insider attacks and OT protocol exploits. Current cyber security solutions are largely domain specific, and do not have a unified approach for cross domain threat correlation, adaptive response orchestration and proactive cyber resilience. In this regard, this study introduces a novel framework called Cross-Domain Cyber Resilience Framework (CD-CRF) that combines multi-domain telemetry fusion, behavioral anomaly detection, intelligent threat deduction, probabilistic risk scoring, and adaptive response orchestration under a single architecture. The framework utilizes signature independent behavioral analytics and cross domain threat correlation with identification of complex multi-stage attacks in heterogeneous Home, IT and OT environments. Experimental assessment was performed with a set of heterogenous cybersecurity data sets, including intrusion detection logs, traces of ransomware activities, IoT botnet traffic, SCADA/ICS telemetry, authentication data and communication data for malware. The proposed CD-CRF successfully reduced the false positive rate to 1.8%, and attained a detection accuracy of 98.6%, threat prediction rate of 94.8% and a cross-domain correlation efficiency of 97.1%. Moreover, it had a response time of 120ms, about 50% faster mitigation than traditional methods, and statistically significantly outperformed GCSM and CAT and TinyML models (p < 0.05). The results show that CD-CRF improves cyber situational awareness, it increases the ability to detect threats early, it decreases operational risks, and it offers scalable, adaptive cyber resilience solution to converged IT–OT environments.