• DocumentCode
    2694509
  • Title

    Immunity diversity based multi-agent intrusion detection

  • Author

    Gu, Yu ; Zhao, Jiashu ; Liang, Dong ; Xu, Zongben

  • Author_Institution
    Xi´´an Jiaotong Univ., Xi´´an
  • fYear
    2007
  • fDate
    25-28 Sept. 2007
  • Firstpage
    3404
  • Lastpage
    3409
  • Abstract
    In this paper, we propose a new method combining artificial immune with support vector machine for intrusion detection, where SVM is used as a core classification algorithm for detector. We introduce immunity diversity concept and we utilize immunity approach to create diversity detectors. We embed detector in Agents in use of the communication mechanism between the Agents, integrate each detection Agent´s result to get the judgment of intrusion detection. This distributing character makes a more robust system. Experiments show that this approach has higher detection accuracy than single SVM and Bagging.
  • Keywords
    artificial immune systems; multi-agent systems; pattern classification; security of data; support vector machines; agent communication; artificial immune; classification algorithm; immunity diversity; multiagent intrusion detection; support vector machine; Evolutionary computation; Intrusion detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1339-3
  • Electronic_ISBN
    978-1-4244-1340-9
  • Type

    conf

  • DOI
    10.1109/CEC.2007.4424912
  • Filename
    4424912