Article
A Comparative Analysis on Hybrid SVM for Network Intrusion Detection System
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Abstract
Rapid growth in technology, not only makes smoother the life style, but also reveals a lot of security issues. Day by day changing of attack types distracts not only organizations, companies but also the people who are using network services for their daily needs. Intrusion Detection Systems (IDS) have been developed to avoid financial losses caused by network attacks. KDD CUP 99, NSL-KDD, KYOTO 2006+, CIDDS-01 etc., some of the Intrusion Datasets available for researchers to test and develop their IDS models. In this paper, an attempt is made to compare the effect of various SVM Kernel based models and Hybrid kernel based models etc., on CIDDS-01 dataset. Results were drawn.
Keywords
IDS, Machine Learning, Support Vector Model, Kyoto 2006+ dataset, CIDDS-01, Intrusion Detection System
Citation
Gaddam, V. & Gatram, R. B. (2021). A comparative analysis on hybrid SVM for network intrusion detection system. Turkish Journal of Computer and Mathematics Education, 12(2), 2674–2679.
V. Gaddam and R. B. Gatram, “A comparative analysis on hybrid SVM for network intrusion detection system,” Turkish Journal of Computer and Mathematics Education, vol. 12, no. 2, pp. 2674–2679, 2021.
Gaddam V, Gatram RB. A comparative analysis on hybrid SVM for network intrusion detection system. Turkish Journal of Computer and Mathematics Education. 2021;12(2):2674–2679.
Gaddam, V. and Gatram, R. B. (2021), ‘A comparative analysis on hybrid SVM for network intrusion detection system’, Turkish Journal of Computer and Mathematics Education, 12(2), pp. 2674–2679.
Gaddam, Venugopal, and Ramamohan Babu Gatram. “A Comparative Analysis on Hybrid SVM for Network Intrusion Detection System.” Turkish Journal of Computer and Mathematics Education, vol. 12, no. 2, 2021, pp. 2674–2679.
Gaddam, Venugopal, and Ramamohan Babu Gatram. “A Comparative Analysis on Hybrid SVM for Network Intrusion Detection System.” Turkish Journal of Computer and Mathematics Education 12, no. 2 (2021): 2674–2679.
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Published by: Engineering Journals


