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A Hybrid Model for Immune Inspired Network Intrusion Detection

  • Robert L. Fanelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5132)

Abstract

This paper introduces a hybrid model for network intrusion detection that combines artificial immune system methods with conventional information security methods. The Network Threat Recognition with Immune Inspired Anomaly Detection, or NetTRIIAD, model incorporates misuse-based intrusion detection and network monitoring applications into an innate immune capability inspired by the immunological Danger Model. Experimentation on a prototype NetTRIIAD implementation demonstrates improved detection accuracy in comparison with misuse-based intrusion detection. Areas for future investigation and improvement to the model are also discussed.

Keywords

Intrusion Detection Anomaly Detection Artificial Immune System Network Intrusion Detection Dendritic Cell Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Robert L. Fanelli
    • 1
  1. 1.Department of Information and Computer ScienceUniversity of Hawaii at ManoaHonoluluUSA

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