Anomaly Detection of Security Threats to Cyber-Physical Systems: A Study

17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)(2022)

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摘要
As the presence of Cyber-Physical Systems (CPS) becomes ubiquitous throughout all facets of modern society, malicious attacks by hostile actors have increased exponentially in recent years. Attacks on critical national infrastructure (CNI) such as oil pipelines or electrical power grids have become commonplace, as increased connectivity to the public internet increases the attack surface of CPS. This paper presents a study of the current academic literature describing the state of the art for anomaly detection of security threats to Cyber-Physical Systems, with a focus on life safety issues for industrial control networks (ICS), with the goal of improving the accuracy of anomaly detection. As a new contribution, this paper also identifies outstanding challenges in the field, and maps selected challenges to potential solutions and/or opportunities for further research.
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关键词
Cyber-physical systems security, IoT security, SCADA security, AI/ML in CPS, Human-in-the-loop cyber-physical systems (HitL-CPS), Anomaly detection in CPS
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