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.KeywordsIntrusion DetectionAnomaly DetectionArtificial Immune SystemNetwork Intrusion DetectionDendritic Cell AlgorithmThese 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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