• DocumentCode
    2141540
  • Title

    Real time intrusion prediction, detection and prevention programs

  • Author

    Abraham, Ajith

  • Author_Institution
    Norwegian Center of Excellence, Norwegian Univ. of Sci. & Technol., Trondheim
  • fYear
    2008
  • fDate
    17-20 June 2008
  • Abstract
    An intrusion detection program (IDP) analyzes what happens or has happened during an execution and tries to find indications that the computer has been misused. In this talk, we present some of the challenges in designing efficient intrusion detection systems (IDS) using nature inspired computation techniques, which could provide high accuracy, low false alarm rate and reduced number of features. Then we present some recent research results of developing distributed intrusion detection systems using genetic programming techniques. Further, we illustrate how intruder behavior could be captured using hidden Markov model and predict possible serious intrusions. Finally we illustrate the role of online risk assessment for intrusion prevention systems and some associated results.
  • Keywords
    genetic algorithms; hidden Markov models; risk management; security of data; distributed intrusion detection systems; genetic programming; hidden Markov model; intrusion detection program; online risk assessment; real time intrusion detection; real time intrusion prediction; real time intrusion prevention; Competitive intelligence; Computational intelligence; Data mining; Data security; Hidden Markov models; Hybrid intelligent systems; Information security; Intrusion detection; Risk management; Web services;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-2414-6
  • Electronic_ISBN
    978-1-4244-2415-3
  • Type

    conf

  • DOI
    10.1109/ISI.2008.4565018
  • Filename
    4565018