Authors:
G Kishor Kumar,R Raja Kumar,K.Nageswara Reddy,P.Arun Babu,DOI NO:
https://doi.org/10.26782/jmcms.spl.5/2020.01.00009Keywords:
Classification,svm,ensemble techniques,intrusion detection,correlation coefficient,Abstract
In this paper, we introduce, “an ensemble of Support Vector Machines (SVM) using Fuzzy-PAM” for network-based intrusion detection. First, the given set of features in a data set is partitioned into blocks or clusters based on correlation coefficient values between pairs of features or attributes. Then the data set is projected onto these feature set to obtain various data sets. SVM is applied on each data set. The given query pattern is also projected onto the feature set and the decision of each SVM is obtained. Weightage is given to each cluster, which is combined with decision of each SVM to obtain a final decision for classifying the given query. We shown the results of applying an ensemble of Support Vector Machines to 1999 KDD Cup data set.Refference:
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