LOW VOLTAGE APPARATUS ›› 2021, Vol. 0 ›› Issue (8): 16-23.doi: 10.16628/j.cnki.2095-8188.2021.08.004

• Research & Analysis • Previous Articles     Next Articles

Research on Power Information Network Security Situation Awareness Based on LDA-RBF

ZHANG Xiaofei1, ZHANG Daoyin1, ZHENG Luolin1, CHEN Decheng2, FU Rong2   

  1. 1. State Grid Electric Power Research Institute,Nanjing 211106,China
    2. College of Automation,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
  • Received:2021-03-21 Online:2021-08-30 Published:2021-10-14

Abstract:

To accurately predict the security situation of power information network,a network security situation awareness method based on machine learning is proposed.In this method,the network security situation awareness is abstracted as a numerical quantization problem,and a large number of test samples are used as data sources to input the situational awareness model to characterize the perceived results.Based on the linear discriminant analysis (LDA),the test data is preprocessed to optimize the sample data to obtain combined features and find out the best projection.Then the processed data are used as input of RBF neural network to find the nonlinear mapping relation of the network situation value,and the network security situation is quantified.Finally,the effectiveness of the proposed method in the security situation analysis is verified through KDD Cup99 dataset and the cyber attack data in the power information network.

Key words: network security situation awareness, power information network, cyber attack, linear discriminant analysis(LDA), RBF neural network

CLC Number: