Intrusion Detection using An Ensemble of Support Vector Machines

被引：5
|
作者：
Kumar, G. Kishor [1 ]
Kumar, R. Raja [1 ]
Basha, M. Suleman [1 ]
Reddy, K. Nageswara [1 ]
机构：
[1] RGMCET, Dept CSE, Nandyal, India
来源：
JOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES | 2019年
关键词：
Bootstrapping; classification; svm; ensemble techniques; intrusion detection;
D O I：
10.26782/jmcms.spl.3/2019.09.00020
中图分类号：
O3 [力学];
学科分类号：
08 ; 0801 ;
摘要：
This paper "an ensemble of Support Vector Machines (SVM)" for network-based 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., 1999 KDDCupandCreditcarddatasets.
引用
收藏
页码：266 / 275
页数：10
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