• DocumentCode
    2919678
  • Title

    Application of Network Intrusion Detection Based on Fuzzy C-Means Clustering Algorithm

  • Author

    Ren, Wuling ; Cao, Jinzhu ; Wu, Xianjie

  • Author_Institution
    Coll. of Comput. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    19
  • Lastpage
    22
  • Abstract
    Aiming at the problem of higher false positive and missing report rate in network intrusion detection, an intrusion detection method based on clustering algorithm is proposed in this paper. This method applies Fuzzy C-means clustering Algorithm to the detection of network intrusion. Through the building of intrusion detection model, carries out fuzzy partition and the clustering of data, and this will detach normal data and attack data effectively. The experiment shows the feasibility and validity of Fuzzy C-means clustering algorithm.
  • Keywords
    pattern clustering; security of data; data clustering; fuzzy C-means clustering algorithm; fuzzy partition; network intrusion detection; Application software; Clustering algorithms; Computer networks; Educational institutions; Face detection; Fuzzy set theory; Fuzzy sets; Intrusion detection; Partitioning algorithms; Protection; Fuzzy C-means; K-means; Network intrusion detection; Soft partition; fuzzy clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.269
  • Filename
    5369559