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http://dx.doi.org/10.3745/KIPSTC.2007.14-C.1.001

The Hybrid Model using SVM and Decision Tree for Intrusion Detection  

Um, Nam-Kyoung (충북대학교 전자계산학과)
Woo, Sung-Hee (충주대학교 멀티미디어학과)
Lee, Sang-Ho (충북대학교 전기전자컴퓨터공학부)
Publication Information
The KIPS Transactions:PartC / v.14C, no.1, 2007 , pp. 1-6 More about this Journal
Abstract
In order to operate a secure network, it is very important for the network to raise positive detection as well as lower negative detection for reducing the damage from network intrusion. By using SVM on the intrusion detection field, we expect to improve real-time detection of intrusion data. However, due to classification based on calculating values after having expressed input data in vector space by SVM, continuous data type can not be used as any input data. Therefore, we present the hybrid model between SVM and decision tree method to make up for the weak point. Accordingly, we see that intrusion detection rate, F-P error rate, F-N error rate are improved as 5.6%, 0.16%, 0.82%, respectively.
Keywords
SVM; Data Mining; Intrusion Detection System(IDS); Decision Tree;
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  • Reference
1 Ke Wang, Salvatore J. Stolfo, 'One-Class Training for Masquerade Detection', CU Tech Report, April, 2003
2 Zhi-Song Pan, Song-Can Chen, Gen-Bao Hu, Dao-Qiang Zhang, 'Hybrid neural network and C4.5 for misuse detection', Proceedings of Machine Learning and Cybernetics International Conference, Vol.4, pp.2463-2467, Nov., 2003   DOI
3 N. Cristianinian, J. Shawe-Taylor, 'An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods', Cambridge University Press, 2000
4 Srinivas Mukkamala, Guadalupe Janoski, Andrew Sung, 'Multi class support vector machine implementation to intrusion detection', Proceedings of the 2002 International Joint Conference, Vo1.2, May, 2002
5 Sung, A.H. Mukkamala, S. 'Identifying important features for intrusion detection using support vector machines and neural networks', Proceedings of Symposium on Applications and the Internet, Jan., 2003
6 Leslie, Christina, Eleazar Eskin and William Stafford Noble, 'The spectrum kernel: A string kernel for SVM protein classification', Proceedings of the Pacific Symposium on Biocomputing, pp.564-575. Jan., 2002