Citation
Rastegari, Samaneh and Saripan, M. Iqbal and A. Rasid, Mohd Fadlee
(2009)
Detection of denial of service attacks against domain name system using neural networks.
International Journal of Computer Science Issues, 6 (1).
pp. 23-27.
ISSN 1694-0814; ESSN: 1694-07
Abstract
In this paper we introduce an intrusion detection system for Denial of Service (DoS) attacks against Domain Name System (DNS). Our system architecture consists of two most important parts: a statistical preprocessor and a neural network classifier. The preprocessor extracts required statistical features in a shorttime frame from traffic received by the target name server. We compared three different neural networks for detecting and classifying different types of DoS attacks. The proposed system is evaluated in a simulated network and showed that the best performed neural network is a feed-forward backpropagation with an accuracy of 99%.
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Official URL or Download Paper: http://arxiv.org/abs/0912.1815
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Additional Metadata
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Engineering |
| Publisher: | Cornell University Library |
| Keywords: | Network security; Domain name system; Denial of service; Neural network |
| Depositing User: | Nabilah Mustapa |
| Date Deposited: | 12 May 2015 00:29 |
| Last Modified: | 02 Nov 2015 23:22 |
| URI: | http://psasir.upm.edu.my/id/eprint/13930 |
| Statistic Details: | View Download Statistic |
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