• DocumentCode
    3740372
  • Title

    Artificial immune system based intrusion detection

  • Author

    Eman Abd El Raoof Abas;Hatem Abdelkader;Arabi Keshk

  • Author_Institution
    Information System department, Faculty of Computer and Information, Suez Canal University, Egypt
  • fYear
    2015
  • Firstpage
    542
  • Lastpage
    546
  • Abstract
    Due to the growing of internet applications, the needs of internet security are increasing. Intrusion detection system is the primary approaches used for saving systems from internal and external intruders. Several techniques have been applied to intrusion detection system such as artificial neural Network, genetic algorithms, artificial immune system. Most researchers suggested improving the intrusion detection performance and accuracy. In this paper, we used artificial immune system network based intrusion detection. In our framework we suggest using GureKddcup database set for intrusion detection and apply R-chunk algorithm of artificial immune system technique, it is used for anomaly detection .An optimized feature selection of rough set theory used for enhancing time consuming.
  • Keywords
    "Immune system","Databases","Floods"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Information Systems (ICICIS), 2015 IEEE Seventh International Conference on
  • Print_ISBN
    978-1-5090-1949-6
  • Type

    conf

  • DOI
    10.1109/IntelCIS.2015.7397274
  • Filename
    7397274