• DocumentCode
    3267233
  • Title

    Cascaded intrusion detection using an improved clustering method

  • Author

    Bao, Zhen ; He, Di

  • Author_Institution
    Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2009
  • fDate
    19-21 Jan. 2009
  • Firstpage
    113
  • Lastpage
    116
  • Abstract
    An improved clustering method used for cascaded intrusion detection is proposed in this paper. It can detect different kinds of intrusions by arranging the processing framework in a cascaded way, based on which we can abstract corresponding features to achieve clustering. Computer simulations based on the 1999 KDD CUP dataset show the effectiveness of the proposed approach in detecting various intrusions and superiority to other clustering methods.
  • Keywords
    pattern clustering; security of data; KDD CUP dataset; cascaded intrusion detection; improved clustering method; Clustering methods; Computer networks; Computer security; Computer simulation; Data security; Helium; Intrusion detection; Neural networks; Support vector machines; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microelectronics & Electronics, 2009. PrimeAsia 2009. Asia Pacific Conference on Postgraduate Research in
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4668-1
  • Electronic_ISBN
    978-1-4244-4669-8
  • Type

    conf

  • DOI
    10.1109/PRIMEASIA.2009.5397433
  • Filename
    5397433
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3267233