An Ensemble Classifier Approach on Different Feature Selection Methods for Intrusion Detection-Reference-Cited by-同舟云学术

An Ensemble Classifier Approach on Different Feature Selection Methods for Intrusion Detection

Published:2018 Issue: Volume: Page:442-451
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
Short-container-title:

Author:

Vinutha H. P.,Poornima B.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-10-7512-4_44

Reference19 articles.

1. Vinutha H P and Poornima B: A Survey—Comparative Study on Intrusion Detection System, IJARCCE, Vol 4, Issue 7, July 2015, ISSN 2778-1021.

2. K. Umamaheswari and S. Janakiraman: Machine Learning in Networking Intrusion Detection System, ARPN journal of Engineering and Applied Sciences, Vol 11, No 2, January 2016, ISSN 1891-6608.

3. Rajender Kaur, Monika Sachdeva and Gulshan Kumar: An Empirical Analysis of Classification Approaches for Feature Selection in Intrusion Detection, IJARCSSE, Issue 9, Vol 6, September 2016, ISSN: 2277 128X.

4. Samah Osama M Kamel, Nadia H Hegazi, Hany M Harb, Adl Y S Tag El Dein, Hala Hala M Abd El Kader: AdaBoost Ensemble Learning Technique for Optimal Feature Subset Selection, IJCNCS, Vol 4, No 1, January 2016, 1–11.

5. Annkita Patel, Risha Tiwari: Bagging Ensemble Technique for Intrusion Detection System, International Journal for Technological Research in Engineering, Issue 4, Vol 2, December 2014, ISSN 2347-2718.

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