Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 588-593.doi: 10.11896/jsjkx.210200151

• Information Security • Previous Articles     Next Articles

Quantitative Method of Power Information Network Security Situation Based on Evolutionary Neural Network

LYU Peng-peng, WANG Shao-ying, ZHOU Wen-fang, LIAN Yang-yang, GAO Li-fang   

  1. Information & Telecommunications Branch,State Grid Hebei Electric Power Co.,Ltd.,Shijiazhuang 050000,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:LYU Peng-peng,born in 1988,engineer.His main research interests include operation and maintenance of electric power information system and network security.
  • Supported by:
    Science and Technology Project of State Grid Hebei Electric Power Co.,Ltd. (kj2019-042).

Abstract: Electric power information networks are facing increasingly severe threats of cyber attacks.Traditional quantification methods of network security situation only analyze from the perspective of network performance,ignoring the impact of the importance of various power application services on the security situation,making it difficult for the quantitative results to fully reflect the power information Cyber risk status.This paper proposes a power information network security situation quantification method based on evolutionary neural networks.First,by analyzing the characteristics of power communication network applications,a power communication network-oriented security situation architecture(PIN-NSSQ)is designed.Secondly,Starting from the three dimensions ofnetwork reliability,threat and vulnerability,combined with the importance of power business,a coupled and interconnected spatial element index system is established,to realize the mathematical representation of key element indicators.Then,integrating the BP neural network optimized by genetic evolution algorithm into the calculation process of element indicators,a power information network security situation quantification model based on evolutionary neural network is constructed to effectively realize the efficient calculation and precise quantification of the process of comprehensive perception of the power information network security situation.Finally,a simulation experiment environment is built according to a certain power department network topology to verify The effectiveness and robustness of the method proposed in the article.

Key words: Evolutionary neural network, Mathematical representation, Network security, Power information network, Situational awareness

CLC Number: 

  • TM732
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