identification of resulting anomalies in the process dynamics of the underlying ICS. Unlike
existing anomaly detectors based on an abstract knowledge acquired from operational data,
PbNN utilizes the design knowledge of ICS to learn the complex relationships among the
correlated components. Such relationships are accurately modeled using operational data
through the application of the deep convolution neural network. The proposed detector was …