• DocumentCode
    3592978
  • Title

    Improved Method for Network Danger Evaluation Based on Immunology Principle

  • Author

    Yang, Jin ; Jin, Peng ; Hong, YanWei ; Luo, Gang

  • Author_Institution
    Dept. of Comput. Sci., LeShan Normal Univ., Leshan, China
  • Volume
    4
  • fYear
    2009
  • Firstpage
    47
  • Lastpage
    51
  • Abstract
    This paper proposes an improved immunological surveillance for network danger evaluation model, focusing on intrusion detection and countermeasures with respect to widely-used networks. An improved intrusion detection mechanism based on self-tolerance, clone selection, and immune surveillance is established. A new network security evaluation method using antibody concentration to quantitatively analyze the degree of intrusion danger level is presented. Additionally, this new hierarchical management framework of the proposed model adopt to improve the detection efficiency and to overcome the shortcoming of the local optimum. The experimental results show that the proposed model is a good solution for network security evaluation.
  • Keywords
    security of data; antibody concentration; clone selection; hierarchical management framework; immunological surveillance; immunology principle; intrusion detection; network danger evaluation; network security evaluation; self-tolerance; Artificial immune systems; Biological system modeling; Cloning; Computer networks; Computer science; Detectors; Immune system; Intrusion detection; Protocols; Surveillance; Artificial Immune system (AIS); Intrusion Detection System; Network Security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2009. ICNC '09. Fifth International Conference on
  • Print_ISBN
    978-0-7695-3736-8
  • Type

    conf

  • DOI
    10.1109/ICNC.2009.169
  • Filename
    5363061