Towards Self-defending Mechanisms Using Data Mining in the EFIPSANS Framework

  • Krzysztof Cabaj
  • Krzysztof Szczypiorski
  • Sheila Becker
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 80)


In currently used networks there are no self-protection or autonomous defending mechanisms. This situation leads to the spread of self-propagating malware, which causes even more dangerous, and significant threats i.e. Botnets. In the EFIPSANS project a new architecture that includes self-* functionalities is introduced. Self-defending functionality, using data mining approach detects and reacts to some of network threats.


Minimal Support Mining Association Rule Data Mining Technique Data Mining Approach Malicious Activity 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Krzysztof Cabaj
    • 1
  • Krzysztof Szczypiorski
    • 1
  • Sheila Becker
    • 2
  1. 1.Warsaw University of TechnologyWarsawPoland
  2. 2.University of LuxembourgLuxembourg

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