Anomaly Intrusion Detection System for SCADA Based Substation Network.

Abstract—The Supervisory Control and Data Acquisition (SCADA) system play a significant role in smart grid communication system. However, emerging cyber security vulnerabilities of SCADA system has become urgent issue for smart grid monitoring, protection, and control. This paper evaluates the possible use of Multilayer Perceptron (MLP) Deep Neural network and captured substation dataset to developed well trained anomaly intrusion detection system (IDS) that can be used to monitor network traffics, host levels and proactively detect cyber intrusions in SCADA system of substation network. The evaluation results of this IDS have shown higher detection accuracy and can effectively detect cyber threats in smart grid.

Index Terms— Cyber Security, SCADA System, Intrusion Detection, Smart grid.