IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems
Industrial Internet systems face increasing threats from sophisticated industrial control system (ICS) attacks, resulting in critical safety incidents. However, existing tools exhibit limited effectiveness in real-time anomaly detection due to the complex dependencies among sensors and actuators. To tackle this, we present IstGPT, the first industrial anomaly detection tool based on LLMs and graph learning to provide real-time protection against a wide range of ICS attacks. IstGPT achieves fine-grained and precise modeling on spatial-temporal dependencies in industrial cyber-physical systems. It first leverages industrial multi-modal knowledge, including operational data, technical docume...
| Authors | Yuchen Zhang, Ning Xi, Pengbin Feng et al. |
|---|---|
| Primary category | cs.CR |
| Published | 1 June 2026 |
| Last updated at source | 1 June 2026 |
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