Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6): 338-342.doi: 10.11896/jsjkx.201200239

• Information Security • Previous Articles     Next Articles

Network Security Situation Assessment Based on Genetic Optimized PNN Neural Network

WANG Jin-heng1, SHAN Zhi-long2, TAN Han-song3, WANG Yu-lin1   

  1. 1 School of Computer Science & Engineering,Guangzhou Institute of Science and Technology,Guangzhou 510540,China
    2 School of Computer Science,South China Normal University,Guangzhou 510631,China
    3 School of Computer Science,Central South University,Changsha 410006,China
  • Received:2020-12-31 Revised:2021-03-06 Online:2021-06-15 Published:2021-06-03
  • About author:WANG Jin-heng,born in 1982,master,lecturer.Her main research interests include computer network technology,artificial intelligence and cloud computing.(11403404@qq.com)
    WANG Yu-lin,born in 1982,master,associate professor.His main research interests include network security and cloud computing.
  • Supported by:
    National Natural Science Foundation of China(61671213),Quality Engineering Construction Project of Guangdong Province,China(2020SZL02) and Teaching Reform and Construction Project of Guangdong Province, China(2018SJG04).

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Abstract: In order to improve the performance of network security situation assessment,this paper presents a network security situation assessment method based on genetic optimization probabilistic neural network.Firstly,In the process of network security situation assessment modeling,according to the characteristics of network security situation and common evaluation levels,the network security situation assessment model of PNN neural network is established,and the advantages of PNN neural network in fine-grained network security situation assessment are fully exploited.Then,in order to prevent the slow convergence caused by the fine-grained evaluation of network security situation parameters,the correction factors of PNN are left,and then the stable PNN network security situation assessment model is obtained by iterative training of PNN neural network.Experiments show that compared with the traditional PNN neural network algorithm,by using genetic algorithm to optimize the PNN network security situation assessment classification,evaluation accuracy is higher,average accuracy rate is more than 90%,and training speed is faster.

Key words: Genetic algorithm, Network attack, Network security situation, Probabilistic neural network

CLC Number: 

  • TP393.08
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