• DocumentCode
    2300179
  • Title

    Intrusion Detection System Using Self-Organizing Maps

  • Author

    Alsulaiman, Mansour M. ; Alyahya, Aasem N. ; Alkharboush, Raed A. ; Alghafis, Nasser S.

  • Author_Institution
    Coll. of Comput. & Inf. Sci., King Saud Univ., Riyadh, Saudi Arabia
  • fYear
    2009
  • fDate
    19-21 Oct. 2009
  • Firstpage
    397
  • Lastpage
    402
  • Abstract
    Internet became one of life´s basics in these days. More networks are connected to the Internet every day, which increases the amount of valuable data and the number of resources that can be attacked. Some systems have been designed and developed to secure these data and prevent attacks on resources. Unfortunately, new attacks are being created everyday, which make it hard to design a system that will catch these attacks. The need is not only for preventing the attack but also for detecting such attacks if it happened. Intrusion detection systems is built to do this task and complement other security systems. In this paper we build an intrusion detection system using a well known unsupervised neural network, namely Kohonen maps. We present the solution by some researchers then propose two enhancements. The enhancement we did gave good result and was able to solve some off the shortcomings of available solution, namely high value of false positive.
  • Keywords
    security of data; self-organising feature maps; unsupervised learning; Internet; Kohonen map; high value-of-false positive; intrusion detection system; neural network; self-organizing map; unsupervised learning algorithm; Computer networks; Computer security; Data security; Educational institutions; Information analysis; Information security; Intrusion detection; Neural networks; Self organizing feature maps; Telecommunication traffic; Detection system; Intrusion; Intrusion Detection system; hierarchical SOM; self organizing maps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Network and System Security, 2009. NSS '09. Third International Conference on
  • Conference_Location
    Gold Coast, QLD
  • Print_ISBN
    978-1-4244-5087-9
  • Electronic_ISBN
    978-0-7695-3838-9
  • Type

    conf

  • DOI
    10.1109/NSS.2009.62
  • Filename
    5319303