• DocumentCode
    3272427
  • Title

    Genetic Algorithm Rule Definition for Denial of Services Network Intrusion Detection

  • Author

    Wang, Yong ; Gu, Dawu ; Tian, XiuXia ; Li, Jing

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
  • Volume
    1
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    99
  • Lastpage
    102
  • Abstract
    Many previous genetic algorithm methods can get much better example results in KDD cup 99 dataset. In the real intrusion detection system, the software needs update the rule even everyday. In this paper, we expand previous work and present a fitness function, propose an efficient rule generator for denial of services of network intrusion detection. We use more chromosomes with relevant features and more rule generator. As such, the rules generated by our algorithm are suitable to continuously changing misuse detection. In order to verify our approach, we tested our proposal with KDD Cup99 dataset, The experimental results show that the proposed approach is an efficient way in network intrusion detection.
  • Keywords
    data mining; genetic algorithms; knowledge based systems; security of data; denial of service; fitness function; genetic algorithm rule definition; knowledge discovery; network intrusion detection; Biological cells; Clustering algorithms; Computational intelligence; Computer crime; Computer science; Genetic algorithms; Intrusion detection; Software systems; Support vector machine classification; Support vector machines; denial of services; genetic algorithm; network intrusion detection; rule definition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3645-3
  • Type

    conf

  • DOI
    10.1109/CINC.2009.106
  • Filename
    5231405