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cs.CR2026
What the Detector Can See: Evaluating CPS Anomaly Detectors Independently of the Decision Rule
Peiran Shi, Jian Xiang, Xiang Zhang +1
Anomaly detectors are often the last line of defense for cyber-physical systems (CPS). But detectors built in very different ways, from deep neural networks to invariant templates,…
cs.CR2025
Few-Shot Learning-Based Cyber Incident Detection with Augmented Context Intelligence
Fei Zuo, Junghwan Rhee, Yung Ryn Choe +2
In recent years, the adoption of cloud services has been expanding at an unprecedented rate. As more and more organizations migrate or deploy their businesses to the cloud, a multi…
cs.CR2024★ 2 cited
INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection
Danial Abshari, Peiran Shi, Chenglong Fu +2
Cyber-Physical Systems (CPS) are vulnerable to cyber-physical attacks that violate physical laws. While invariant-based anomaly detection is effective, existing methods are limited…