What does this research mean for the field?

An AI-driven security assessment framework effectively detects threats, monitors system activities, and mitigates real-time risks in cyber-physical systems while ensuring compliance with major security standards. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To establish and evaluate an AI-driven security assessment framework capable of identifying vulnerabilities, mitigating physical-digital threats, and ensuring standards compliance in cyber-physical systems.

August 29, 2026SensorsOpen Access

AI-Driven Problem Solving for Cyber-Physical Systems Security: An Assessment Framework

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Authors

VKVikram KulothunganCapitol Technology University DGDeepti GuptaTexas A&M University – Central Texas RDRaju DhakalEmbry–Riddle Aeronautical University

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Implication

Systems evaluation demonstrates an AI-driven security framework detects real-time threats across cyber-physical infrastructure, highlighting improved protection against ransomware and...

Key Points

To establish and evaluate an AI-driven security assessment framework capable of identifying vulnerabilities, mitigating physical-digital threats, and ensuring standards compliance in cyber-physical systems.
Surveyed existing CPS risk assessment methodologies across healthcare, automotive, energy, and critical infrastructure sectors.
Engineered an AI-driven framework for continuous operational monitoring, real-time threat detection, and automated compliance mapping to NIST, IEC 62443, ISO 21434, and GDPR.
Evaluated a prototype implementation across multiple real-world attack vectors, including industrial malware, automotive hacking, and an active ransomware attack simulation on a smart manufacturing plant.
Demonstrated improved threat identification for digital-physical vulnerabilities, including sensor manipulation and machine learning model supply chain exploits.
Maintained smart manufacturing plant operational continuity and regulatory compliance during a live simulated ransomware deployment.

Cite This Study

Kulothungan et al. (2026) studied this question.

synapsesocial.com/papers/6a92995f8e5d7d1fc0c11480 https://doi.org/10.3390/s26175412

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Implication

Systems evaluation demonstrates an AI-driven security framework detects real-time threats across cyber-physical infrastructure, highlighting improved protection against ransomware and...

AI-Driven Problem Solving for Cyber-Physical Systems Security: An Assessment Framework

Discussion

Member takes

Implication

Key Points

Cite This Study

AI-Driven Problem Solving for Cyber-Physical Systems Security: An Assessment Framework

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider