Detection of denial of service attacks against domain name system using neural networks

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 feat...

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Main Authors: Rastegari, Samaneh, Saripan, M. Iqbal, A. Rasid, Mohd Fadlee
Format: Article
Language:English
Published: Cornell University Library 2009
Online Access:http://psasir.upm.edu.my/id/eprint/13930/
http://psasir.upm.edu.my/id/eprint/13930/1/Detection%20of%20denial%20of%20service%20attacks%20against%20domain%20name%20system%20using%20neural%20networks.pdf
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author Rastegari, Samaneh
Saripan, M. Iqbal
A. Rasid, Mohd Fadlee
author_facet Rastegari, Samaneh
Saripan, M. Iqbal
A. Rasid, Mohd Fadlee
author_sort Rastegari, Samaneh
building UPM Institutional Repository
collection Online Access
description 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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institution_category Local University
language English
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publisher Cornell University Library
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spelling upm-139302015-11-02T23:22:40Z http://psasir.upm.edu.my/id/eprint/13930/ Detection of denial of service attacks against domain name system using neural networks Rastegari, Samaneh Saripan, M. Iqbal A. Rasid, Mohd Fadlee 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%. Cornell University Library 2009-11 Article NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/13930/1/Detection%20of%20denial%20of%20service%20attacks%20against%20domain%20name%20system%20using%20neural%20networks.pdf 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 http://arxiv.org/abs/0912.1815
spellingShingle Rastegari, Samaneh
Saripan, M. Iqbal
A. Rasid, Mohd Fadlee
Detection of denial of service attacks against domain name system using neural networks
title Detection of denial of service attacks against domain name system using neural networks
title_full Detection of denial of service attacks against domain name system using neural networks
title_fullStr Detection of denial of service attacks against domain name system using neural networks
title_full_unstemmed Detection of denial of service attacks against domain name system using neural networks
title_short Detection of denial of service attacks against domain name system using neural networks
title_sort detection of denial of service attacks against domain name system using neural networks
url http://psasir.upm.edu.my/id/eprint/13930/
http://psasir.upm.edu.my/id/eprint/13930/
http://psasir.upm.edu.my/id/eprint/13930/1/Detection%20of%20denial%20of%20service%20attacks%20against%20domain%20name%20system%20using%20neural%20networks.pdf