An Anomaly Detection System for Operational Threats in SCADA System

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Abstract

One of the most dangerous insider threats in a supervisory control and data acquisition (SCADA) system is operational threat. An operational threat occurs when an SCADA operator does not perform his duties, or decides to abuse the privileges in order to perform malicious operations in remote substations. An operational threat on a critical infrastructure has the potential to cause large financial losses and irreparable damages at the national level. In this paper a new alarm-based anomaly detection system has been proposed to detect operational threats in SCADA system. The proposed system uses statistical quality control techniques for detecting anomalies and estimating control limits. The value of anomaly is calculated according to the severity of longed-unresolved alarms. The simulation results in power system SCADA as a case study show effectiveness of proposed system.

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