Published: 2026

Security Challenges and Protection Strategies for Industrial AI Agents: A Comprehensive Survey

CATEGORIES

RISK-BASED PROCESS SAFETY ELEMENTS

Research Summary

Conference survey of LLM-powered industrial AI agents that interface directly with physical processes, safety-critical control systems, and historians. The authors propose a six-category risk taxonomy: model reliability, input manipulation, tool/protocol vulnerabilities, multi-agent collaboration risks, Information Technology/Operational Technology ("IT/OT") convergence risks, and supply-chain integrity. For each category they map incidents, attack vectors, and defense-in-depth controls, and they flag gaps in existing Industrial Control Systems/Operational Technology standards when the actor is a non-deterministic agent rather than a deterministic controller. This is one of the few papers that treats SIS and safety-critical control as first-class agent interfaces and that calls out multi-agent collusion and tool-protocol (MCP/A2A-style) abuse as OT hazards. For a PSM library it supplies the threat taxonomy a HAZOP or cyber-PHA team would use when an agent is added to a node.

AUTHORS

Y. Gong, X. Li, and J. Shi

CITATIONS

Y. Gong, X. Li, and J. Shi, “Security Challenges and Protection Strategies for Industrial AI Agents: A Comprehensive Survey,” in Proc. 6th Int. Conf. Internet of Things and Machine Learning (IoTML 2026), Nanning, China, May 15–17, 2026, doi: 10.1145/3838457.3838551.

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