• DocumentCode
    2850603
  • Title

    Intrusion detection model based on the improved neural network and expert system

  • Author

    Gong, Xingchao ; Guan, Xin

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Liaoning Tech. Univ., Huludao, China
  • fYear
    2012
  • fDate
    24-27 June 2012
  • Firstpage
    191
  • Lastpage
    193
  • Abstract
    This paper shows a intrusion detection model that combines the BP networks and the expert system aiming at the bad effect of a single detection model .This model uses the improvement the BP neural network, simultaneously through the similar expert solves the actual problem inference mechanism, creat a neural network expert system model. The experiment simulation show that this model has less iteration times, quicker convergence rate?higher detection rate and sufficient availability, at present mainly applied in the mine network security.
  • Keywords
    backpropagation; convergence; expert systems; inference mechanisms; iterative methods; neural nets; security of data; BP neural network; convergence rate; detection rate; expert system; inference mechanism; intrusion detection model; iteration times; mine network security; Engines; Probes; BP Network; Expert System; Intrusion Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Electronics Engineering (EEESYM), 2012 IEEE Symposium on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4673-2363-5
  • Type

    conf

  • DOI
    10.1109/EEESym.2012.6258621
  • Filename
    6258621