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Faculty of Engineering & Technology
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Staff Researches

Comparison of classification techniques applied for network intrusion detection and classification

  • Author Name :
    Amira Sayed
  • CoAuthors :
    Sanaa El Ola Hanafi, Aboul ella Hassnaien
  • Source :
    Journal of Applied Logic - Elsevier
  • Research Date :
    11/2016
  • Abstract :
    In a previous research, a multi-agent artificial immune system for network intrusion detection and classification was proposed and tested, where a multi-layer detection and classification process was executed on each agent, for each host in the network. In this paper, we show the experiments that were held to chose the appropriate classifiers by testing different classifiers and comparing them to increase the detection accuracy and obtain more information on the detected anomalies.
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