An Intrusion Detection System Based On Support Vector Machine Using Hierarchical Clustering And Genetic Algorithm

An NIDS system based on SVM ,GA and Hierarchical Clustering is proposed.GA along with hierarchical clustering is used to provide fewer,efficient and abstraced instances of the KDD Cup 1999 dataset to SVM for further processing.GA is used to eliminate the unimportant feature and BIRCH hierarchical clustering is used to provide optimal instances of the data set to the SVM.Due to this optimal instances, SVM will be able to classify the network traffic data more accurately and precisely . This system try to reduce the detection time of r2l,u2r,probe and DoS atack and increase in the accuracy