Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks

Abstract

This paper presents a novel unsupervised approach to detect cyber attacks in Cyber-Physical Systems (CPS). We describe an unsupervised learning approach using a Recurrent Neural network which is a time series predictor as our model. We then use the Cumulative Sum method to identify anomalies in a replicate of a water treatment plant. The proposed method not… (More)
DOI: 10.1109/HASE.2017.36

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