• DocumentCode
    1868515
  • Title

    Intrusion detection research based on improved PSO and SVM

  • Author

    Liu Ning ; Zhao Jianhua

  • Author_Institution
    Department of Computer Science, ShangLuo University, 726000, China
  • fYear
    2012
  • fDate
    3-5 March 2012
  • Firstpage
    1263
  • Lastpage
    1266
  • Abstract
    Based on the thought of crossover operation and mutation operation in genetic algorithm, this paper improves particle swarm optimization algorithm. The improved particle swarm optimization algorithm is used to optimize penalty parameter c and kernel function parameters g of SVM and the optimized model named new-PSO-SVM is established. KDD Cup 99 intrusion detection data set is used to carry out experiment. The results show that PSO optimization improves the classification accuracy rate of SVM.
  • Keywords
    Intrusion detection; Particle swarm optimization algorithm; Support vector machine;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
  • Conference_Location
    Xiamen
  • Electronic_ISBN
    978-1-84919-537-9
  • Type

    conf

  • DOI
    10.1049/cp.2012.1209
  • Filename
    6492816