• DocumentCode
    2719809
  • Title

    Network Immunity: What can we learn from nature for network protection?

  • Author

    Kleis, Michael ; Hirsch, Thomas ; Zseby, Tanja

  • Author_Institution
    Fraunhofer Inst. FOKUS, Berlin
  • fYear
    2007
  • fDate
    10-12 Dec. 2007
  • Firstpage
    283
  • Lastpage
    286
  • Abstract
    In this paper we analyze network immunity as a bio-inspired approach for detecting anomalies in communication networks. We briefly review the basic methods of artificial immune systems (AIS), identify their strengths and weaknesses, and evaluate their possible applications to intrusion detection in computer networks. After an overview of related work from the area of intrusion detection we collect key challenges anticipated for the realization of network immunity based on AIS.
  • Keywords
    artificial immune systems; security of data; telecommunication computing; telecommunication networks; telecommunication security; artificial immune systems; communication networks; network immunity; network protection; Adaptive systems; Communication system security; Computer networks; Computer security; Face detection; Humans; Immune system; Intrusion detection; Pathogens; Protection; Anomaly Detection; Artificial Immune Systems; Network Intrusion Detection; Survey;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Models of Network, Information and Computing Systems, 2007. Bionetics 2007. 2nd
  • Conference_Location
    Budapest
  • Print_ISBN
    978-963-9799-05-9
  • Electronic_ISBN
    978-963-9799-05-9
  • Type

    conf

  • DOI
    10.1109/BIMNICS.2007.4610128
  • Filename
    4610128