• DocumentCode
    1943191
  • Title

    Combining Self-Organizing Map Algorithms for Robust and Scalable Intrusion Detection

  • Author

    Albayrak, Sahin ; Scheel, Christian ; Milosevic, Dragan ; Müller, Achim

  • Author_Institution
    DAI-Labor, TU Berlin
  • Volume
    2
  • fYear
    2005
  • fDate
    28-30 Nov. 2005
  • Firstpage
    123
  • Lastpage
    130
  • Abstract
    In the field of intrusion detection systems, the aspect of anomaly detection is very important, and consequently there are many approaches that address these security issues. The usage of self-organizing map (SOM) makes a foundation for some of these approaches, which consequently often have problems to cope with the requirements of huge nowadays networks. The proposed approach focuses on improving the usage of SOMs for anomaly detection, by combining the strengths of different SOM algorithms. The performed evaluations have shown the necessity of paying attention to different aspects, coming along with network nodes, to individually choose the best matching SOM for each node´s anomaly detection
  • Keywords
    security of data; self-organising feature maps; anomaly detection; intrusion detection system; security issues; self-organizing map algorithm; Inspection; Intrusion detection; Invasive software; Laboratories; Neural networks; Organizing; Performance evaluation; Protection; Robustness; Unsupervised learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
  • Conference_Location
    Vienna
  • Print_ISBN
    0-7695-2504-0
  • Type

    conf

  • DOI
    10.1109/CIMCA.2005.1631456
  • Filename
    1631456