Intrusion Detection using An Ensemble of Support Vector Machines


G Kishor Kumar,R Raja Kumar,M Suleman Basha,K Nageswara Reddy,



Bootstrapping,classification,svm,ensemble techniques,intrusion detection,


This paper “an ensemble of Support Vector Machines (SVM)” for networkbased intrusion detection. Bootstrapping is applied to derive various training sets from the given training set. Then a SVM is derived for each training set. The decisions of all SVMs is taken and majority voting is considered to classify the given query pattern as a normal or an anomalous one. We have shown the results of applying an ensemble of Support Vector Machines to the two standard data sets,viz.,1999KDDCupandCreditcarddatasets.


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