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What is Ensemble Classifiers for Intrusion Detection about?

This document summarizes an academic paper that proposes using an ensemble of classifiers for network intrusion detection. Specifically, it uses Linear Genetic Programming (LGP), Adaptive Neural Fuzzy Inference System (ANFIS), and Random Forest (RF) as individual classifiers. Feature selection is performed prior to classify network traffic into normal, probe, DoS, U2R, and R2L categories. Empirical results show the ensemble approach improves detection accuracy compared to individual classifiers.

Author

EDGAR RODRIGO NAULA LOPEZ

Language

EN