• DocumentCode
    2340945
  • Title

    A Layered Multi-Agent Detection Model for Abnormal Intrusion Based on Danger Theory

  • Author

    Xiao TaoHuang ; Sha Li ; Li QunHuang

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2010
  • fDate
    23-25 April 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A layered multi-agent detection model for abnormal intrusion, based on danger theory, is presented according to the research on the danger theory and artificial immunity. The model, with three layers in the frame, conducts the real time monitoring and danger judgment on the host computer and network resource before it recognizes the nonself, and then the danger signal activates the immunity recognition. The danger judgment conducted by cloud model can recognize the harmful self and harmful nonself effectively, which ensures the system safety and improves the performance of detection system. Thus, the probability of misinformation and omission will decrease to some extent.
  • Keywords
    computer network security; multi-agent systems; probability; abnormal intrusion; artificial immunity; cloud model; danger judgment; danger theory; detection system performance; harmful self; host computer; immunity recognition; layered multiagent detection model; network resource; probability; real time monitoring; system safety; Character generation; Clouds; Computer networks; Computer science; Educational institutions; Entropy; Gaussian distribution; Helium; Immune system; Intrusion detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5315-3
  • Type

    conf

  • DOI
    10.1109/ICBECS.2010.5462467
  • Filename
    5462467