• DocumentCode
    3061951
  • Title

    D-S Evidence Theory and its Data Fusion Application in Intrusion Detection

  • Author

    Tian, Junfeng ; Zhao, Weidong ; Du, Ruizhong ; Zhang, Zhe

  • Author_Institution
    Hebei University, Baoding, China
  • fYear
    2005
  • fDate
    05-08 Dec. 2005
  • Firstpage
    115
  • Lastpage
    119
  • Abstract
    Based on the D-S Evidence Theory and its Data Fusion technology, a new Intrusion Detection Data Fusion Model-IDSDFM is presented. This model can merge alerts of different types of IDSs, make intelligent inference by applying the D-S Evidence Theory, and estimate the current security situation according to the fusion result. Then some IDSs in the network are dynamically adjusted to strengthen the detection of the data that relate to the attack attempt. Consequently, the false positive rate and the false negative rate are effectively reduced, and the detection efficiency of IDS is accordingly improved.
  • Keywords
    Application software; Bayesian methods; Computer science; Data security; Estimation theory; Information security; Intrusion detection; Mathematical model; Mathematics; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. Sixth International Conference on
  • Print_ISBN
    0-7695-2405-2
  • Type

    conf

  • DOI
    10.1109/PDCAT.2005.109
  • Filename
    1578878