• DocumentCode
    2986528
  • Title

    Improved Genetic Algorithm in Intrusion Detection Model Based on Artificial Immune Theory

  • Author

    Jing Xiaopei ; Wang Houxiang ; Han Ruofei ; Li Juan

  • Author_Institution
    Inf. & Electr. Coll., Naval Univ. of Eng., Wuhan, China
  • fYear
    2009
  • fDate
    18-20 Jan. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    After analysis the characteristics of AlS-based intrusion detection system, a new AlS-based intrusion detection model based improved genetic algorithm is established. By utilizing prominent characteristics of genetic algorithm, such as automatic optimizing, global researching, and adaptability, the new model uses genetic operator to improve the candidate detectors generating algorithm and reduce detectors redundancy. The detectors generated by new model have good fitness and better detection ability. Experiments show that this model can effectively increase the true positive rate of the IDS.
  • Keywords
    artificial immune systems; genetic algorithms; security of data; AlS-based intrusion detection system; artificial immune theory; genetic operator; improved genetic algorithm; intrusion detection model; Detectors; Educational institutions; Flowcharts; Genetic algorithms; Genetic engineering; Genetic mutations; Immune system; Information analysis; Intrusion detection; Random number generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5272-9
  • Type

    conf

  • DOI
    10.1109/CNMT.2009.5374541
  • Filename
    5374541