Conflict-driven Hybrid Observer-based Anomaly Detection
Optimization and Control
2017-12-08 v1
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.
Keywords
Cite
@article{arxiv.1712.02396,
title = {Conflict-driven Hybrid Observer-based Anomaly Detection},
author = {Zheng Wang and Farshad Harirchi and Dhananjay Anand and CheeYee Tang and James Moyne and Dawn Tilbury},
journal= {arXiv preprint arXiv:1712.02396},
year = {2017}
}