Intelligent data augmentation for supervised anomaly detection associated with a cyber-physical system

Abstract

A Cyber-Physical System ('CPS') may have monitoring nodes that generate a series of current monitoring node values representing current operation of the CPS. A normal space data source may store, for each monitoring node, a series of normal monitoring node values representing normal operation of the CPS. An abnormal data generation platform may utilize information in the normal space data source and a generative model to create generated abnormal to represent abnormal operation of the CPS. An abnormality detection model creation computer may receive the normal monitoring node values (and generate normal feature vectors) and automatically calculate and output an abnormality detection model including information about a decision boundary created via supervised learning based on the normal feature vectors and the generated abnormal data.