• DocumentCode
    2126793
  • Title

    A Fast Fuzzy Set Intrusion Detection Model

  • Author

    Lin Jianhui ; Huang Tianshu ; Bingjie, Zhao

  • Author_Institution
    Sch. of Electron. Inf., Wuhan Univ., Wuhan
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    601
  • Lastpage
    605
  • Abstract
    Applying the basic fuzzy theory and method into intrusion detection has achieved a series success. In this paper, an intrusion detection model base on fuzzy sets is presented to avoid the sharp boundary problem in rules mining. Considering Apriori algorithm is time-consuming as well as space-consuming; moreover, we propose a new rule mining algorithm base prefix tree (PTBA). PTBA algorithm compress the fuzzy pattern candidate set and frequent set through constructing a tree structure, thus it can save the memory cost of fuzzy pattern candidate and frequent set. Experiments prove that capability and efficiency of IDS model is obviously improved.
  • Keywords
    data mining; fuzzy set theory; security of data; trees (mathematics); PTBA algorithm; apriori algorithm; frequent set; fuzzy pattern candidate set; fuzzy set intrusion detection model; fuzzy theory; prefix tree; rule mining algorithm; rules mining; sharp boundary problem; Data mining; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Information technology; Intrusion detection; Knowledge acquisition; Knowledge engineering; Logistics; Training data; IDS; fuzzy set; prefix tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.21
  • Filename
    4732897