An Intrusion Detection System based on Support Vector Machine using Hierarchical Clustering and Genetic Algorithm

Abstract

This study proposed an SVM based IDS which combines GA, Hierarchical Clustering and SVM techanique.GA is used to preprocess the KDD Cup (1999) data set before SVM training. The proposed system reduces the training time and also achieve better classification of various types of attacks. GA provide the important feature and hierarchical clustering algorithm is used to provide a high quality, abstracted and reduced dataset to SVM for training. This system tries to increase accuracy of probe and u2r attacks. This system is implemented in MATLAB.