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The Assessment Method of Network Security Situation Based on Improved BP Neural Network

  • Gangsong Dong
  • Wencui LiEmail author
  • Shiwen Wang
  • Xiaoyun Zhang
  • JiZhao Lu
  • Xiong Li
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 905)

Abstract

With the popularity of the Internet and the emergence of cloud computing, network security issues have become increasingly prominent. In view of the low efficiency and poor reliability of the existing network security situation assessment methods, this paper proposes a quantitative assessment method based on an improved BP neural network. Aiming at the disadvantages of slow convergence speed, easy oscillation, and local minimum in BP neural network, this paper optimized the algorithm by combining Cuckoo search algorithm, introducing momentum factor and adaptive learning rate. The simulation results show that the improved CS-BPNN algorithm in this paper has fast convergence rate and high evaluation accuracy, which provides a new method for network situation assessment.

Keywords

Network security situation assessment BP neural network Cuckoo search algorithm Momentum factor 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Gangsong Dong
    • 1
  • Wencui Li
    • 1
    Email author
  • Shiwen Wang
    • 1
  • Xiaoyun Zhang
    • 2
  • JiZhao Lu
    • 1
  • Xiong Li
    • 1
  1. 1.Information & Telecommunication Co. of State Grid Henan Electric Power CompanyZhengzhouChina
  2. 2.China Electric Power Equipment and Technology Co. Ltd., Zhengzhou Electric Power Design InstituteZhengzhouChina

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