Improving performance of intrusion detection system using ensemble methods and feature selection-Reference-Cited by-同舟云学术

Improving performance of intrusion detection system using ensemble methods and feature selection

Published:2018-01-29 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Australasian Computer Science Week Multiconference
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Author:

Pham Ngoc Tu¹,Foo Ernest¹,Suriadi Suriadi¹,Jeffrey Helen¹,Lahza Hassan Fareed M¹

Affiliation:

1. Queensland University of Technology, Brisbane, Queensland

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3167918.3167951

Reference20 articles.

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2. Ensemble neural network and k-NN classifiers for intrusion detection;Chaurasia Shalinee;International Journal of Computer Science and Information Technology,2014

3. Experiments with a new boosting algorithm;Freund Yoav;Icml,1996

4. DAREnsemble: Decision Tree and Rule Learner Based Ensemble for Network Intrusion Detection System

5. Hybrid Intrusion Detection Using Ensemble of Classification Methods

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