期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2017
卷号：8
期号：6
页码：703-713
出版社：Engg Journals Publications
摘要：Intrusion Detection System (IDS) has become necessary for the security and privacy of a systemand it takes a major role in network security because of its detection capacity to various types of attacksin the network domain. Recently, Support Vector Machines (SVM) has been applied to provide usefulsolutions for intrusion detection systems. With its many variants for classification, SVM is a state-of-theartmachine learning algorithm and its performance depends on selection of the appropriate parameters.In this paper, we propose a model based on linear and nonlinear kernel SVMs using NSL-KDD dataset.The parameters for SVM are described in the tabular manner. Then by using the NSL-KDD dataset, ourmodel gives the best result i.e., 100% for accuracy (Both Quadratic and Cubic SVMs).
关键词：Intrusion Detection System (IDS); Linear and Nonlinear Support Vector Machines (SVMs);Performance Matrices
