• DocumentCode
    2001711
  • Title

    Towards an Adaptive Intrusion Detection System: A Critical and Comparative Study

  • Author

    Bensefia, Hassina ; Ahmed-Nacer, Mohammed

  • Author_Institution
    Res. Center on the Sci. & Tech. Inf. (CERIST), Algiers, Algeria
  • Volume
    2
  • fYear
    2008
  • fDate
    13-17 Dec. 2008
  • Firstpage
    246
  • Lastpage
    251
  • Abstract
    An intrusion detection system (IDS) that is destined to supervise an environment, must adjust itself according to every change in the environment and be handling every new attack occurrence. This feature is referred to as the adaptability. It makes the IDS a learning system in relation to its target environment, practicing an autonomous and continuous learning of new attacks. This paper develops a critical and comparative study of existing adaptive intrusion detection models. The objective of such study is to be oriented with regard to related works in the aim of building our own vision to add contribution in the IDS adaptability context.
  • Keywords
    learning (artificial intelligence); security of data; adaptive intrusion detection system; autonomous learning; continuous learning; learning system; Adaptive systems; Computational intelligence; Computer science; Computer security; Decision making; Information security; Intrusion detection; Learning systems; Monitoring; Telecommunication traffic; Intrusion detection; adaptability; autonomous learning; incremental learning; new attack patterns;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security, 2008. CIS '08. International Conference on
  • Conference_Location
    Suzhou
  • Print_ISBN
    978-0-7695-3508-1
  • Type

    conf

  • DOI
    10.1109/CIS.2008.94
  • Filename
    4724775