Research on Power Security Early Warning System Based on Improved K-means Algorithm

Abstract

In response to the problem of data acquisition and massive alarm information screening and extraction in the traditional power grid security early warning system under the high-speed network environment, this paper integrates the improved K-means algorithm in the process of clustering analysis module processing alarm data, and analyzes the initial alarm data of intrusion detection system after feature processing and format conversion combined with Weka application platform, and finally obtains more efficient alarm information. The results of many experiments show that the power security early warning system based on the improved K-means clustering algorithm solves the problems existing in the traditional security system, which can largely avoid the problem of system omission and false alarm, and the overall performance of the power security early warning system has been greatly improved.