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arXiv · 1712.02396

Conflict-driven Hybrid Observer-based Anomaly Detection

Zheng Wang·Farshad Harirchi·Dhananjay Anand·CheeYee Tang·James Moyne·Dawn Tilbury
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Abstract

This paper presents an anomaly detection method using a hybrid observer -- which consists of a discrete state observer and a continuous state observer. We focus our attention on anomalies caused by intelligent attacks, which may bypass existing anomaly detection methods because neither the event sequence nor the observed residuals appear to be anomalous. Based on the relation between the continuous and discrete variables, we define three conflict types and give the conditions under which the detection of the anomalies is guaranteed. We call this method conflict-driven anomaly detection. The effectiveness of this method is demonstrated mathematically and illustrated on a Train-Gate (TG) system.

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Zheng Wang, Farshad Harirchi, Dhananjay Anand, CheeYee Tang, James Moyne, Dawn Tilbury. 2017-12-06. Conflict-driven Hybrid Observer-based Anomaly Detection. https://arxiv.org/abs/1712.02396

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