Abstract:Aiming at the problem that the traditional power network traffic detection and security warning system cannot meet the demand in terms of accuracy, timeliness, expansibility, and efficiency in facing of massive high-dimensional data, a Spark based traffic anomaly detection platform for power grid industrial control system is established. The platform takes Spark as its computing framework, which is mainly composed of data acquisition and network traffic deep packet detection protocol parsing module, real-time computing data analysis and processing module, security warning and prediction module, and data storage module, to complete process for traffic anomaly detection. Experimental results show that the platform can effectively detect the abnormal flow, make the safety warning, convenient for staff to make decisions in time. This fully shows that the platform is very suitable for electric control system, can deal with massive amounts of high-dimensional complex data real time analysis and early warning, greatly improve the safety performance of the power grid control system.