• DocumentCode
    2235571
  • Title

    Method of evolutionary neural network-based intrusion detection

  • Author

    Wang, Lina ; Yu, Ge ; Wang, Guoren ; Wang, Dong

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    13
  • Abstract
    Intrusion detection is an important defence to protect the security of computer network systems. With an integrated technique of genetic algorithm and neural network, a method of evolutionary neural networks is proposed to perform intrusion detection in this paper. It is a robust enough, parallel and nonlinear dynamic processing system to satisfy requirements of real-time processing and prediction with high accuracy. With the new method, the structure of the neural network is optimized using a genetic algorithm. The obtained neural network model is thus used for intrusion detection and prealarm with high accuracy
  • Keywords
    authorisation; computer network management; genetic algorithms; nonlinear dynamical systems; parallel algorithms; real-time systems; telecommunication security; accurate prediction; computer network security; evolutionary neural network; genetic algorithm; intrusion detection; nonlinear dynamic system; prealarm; real-time processing; robust parallel processing; Accuracy; Computer networks; Computer security; Genetic algorithms; Intrusion detection; Neural networks; Nonlinear dynamical systems; Protection; Real time systems; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-7010-4
  • Type

    conf

  • DOI
    10.1109/ICII.2001.983487
  • Filename
    983487