• DocumentCode
    2019993
  • Title

    Design of an Immune-inspired Danger Theory Model Based on Fuzzy Set

  • Author

    Hai-Dong, Fu ; Gui-Feng, LI

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Wuhan Univ. of Sci. & Technol., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    17-18 Oct. 2008
  • Firstpage
    133
  • Lastpage
    136
  • Abstract
    An immune-inspired danger theory model based on fuzzy set was proposed in this article. In the model the concept of fuzzy set and degree of membership are presented in the foundation of the "danger" definition in artificial immune system. By carrying on the computation to the degree of danger, it makes the organism to apperceive the danger and simultaneously to make a strategy efficiently. It improves the organism to recognize the "danger" effectively, and then enhances the rate of intrusion detection based on the artificial immune model, and reduces the false alarm.
  • Keywords
    artificial immune systems; fuzzy set theory; security of data; artificial immune system; fuzzy set; immune-inspired danger theory model; intrusion detection; Biological system modeling; Cells (biology); Computational intelligence; Computer science; Educational institutions; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Immune system; Organisms; artificial immune; danger theory; degree of membership; fuzzy set; intrusion detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3311-7
  • Type

    conf

  • DOI
    10.1109/ISCID.2008.97
  • Filename
    4725574