Abstract
This paper presents continued experimentation on the Network Threat Recognition with Immune Inspired Anomaly Detection, or NetTRIIAD, model. This hybrid model combines established network monitoring methods with artificial immune system methods to achieve improved performance. The paper presets experiments investigating the model's performance in detecting novel threats and the performance contribution of the individual components. © 2010 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Fanelli, R. L. (2010). Further experimentation with hybrid immune inspired network intrusion detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6209 LNCS, pp. 264–275). https://doi.org/10.1007/978-3-642-14547-6_21
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