Best hybrid classifiers for intrusion detection

Abstract

We present in this paper an intrusion detection software-system that we have built based on combined statistical and computational models to detect intrusions and classify them as attack or non-attack. More specifically, we build a computational machine to derive optimal parsimonious hybrid model of classifiers in intrusion detection. The classifiers are based on the following classification methods, Naïve Bayes-NB, K-nearest neighbor-K-nn, and Neural networks-NN.