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Applying Neural Network to U2R Attacks

Intrusion detection using artificial neural networks is an ongoing area and thus interest in this field has increased among the researchers. Therefore, in this paper we present a system for tackling User to Root (U2R) attacks using generalized feedforward neural network. A backpropagation algorithm...

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Main Authors: Iftikhar , Ahmad, Azween, Abdullah, Abdullah , S. Alghamdi
Format: Conference or Workshop Item
Published: 2010
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utp.edu.my/3081/1/6.pdf
http://eprints.utp.edu.my/3081/
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id my.utp.eprints.3081
record_format eprints
spelling my.utp.eprints.30812010-11-12T01:19:42Z Applying Neural Network to U2R Attacks Iftikhar , Ahmad Azween, Abdullah Abdullah , S. Alghamdi QA75 Electronic computers. Computer science Intrusion detection using artificial neural networks is an ongoing area and thus interest in this field has increased among the researchers. Therefore, in this paper we present a system for tackling User to Root (U2R) attacks using generalized feedforward neural network. A backpropagation algorithm is used for training and testing purpose. The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. The system is implemented in two phases such as training phase and testing phase. The developed system is applied to different U2R attacks to test its performance. Furthermore, the results indicate that this approach is more precise and accurate in case of false positive, false negative and detection rate. 2010 Conference or Workshop Item NonPeerReviewed application/zip http://eprints.utp.edu.my/3081/1/6.pdf Iftikhar , Ahmad and Azween, Abdullah and Abdullah , S. Alghamdi (2010) Applying Neural Network to U2R Attacks. In: 2010 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010) , 3-6/10, Penang, Malaysia. http://eprints.utp.edu.my/3081/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Iftikhar , Ahmad
Azween, Abdullah
Abdullah , S. Alghamdi
Applying Neural Network to U2R Attacks
description Intrusion detection using artificial neural networks is an ongoing area and thus interest in this field has increased among the researchers. Therefore, in this paper we present a system for tackling User to Root (U2R) attacks using generalized feedforward neural network. A backpropagation algorithm is used for training and testing purpose. The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. The system is implemented in two phases such as training phase and testing phase. The developed system is applied to different U2R attacks to test its performance. Furthermore, the results indicate that this approach is more precise and accurate in case of false positive, false negative and detection rate.
format Conference or Workshop Item
author Iftikhar , Ahmad
Azween, Abdullah
Abdullah , S. Alghamdi
author_facet Iftikhar , Ahmad
Azween, Abdullah
Abdullah , S. Alghamdi
author_sort Iftikhar , Ahmad
title Applying Neural Network to U2R Attacks
title_short Applying Neural Network to U2R Attacks
title_full Applying Neural Network to U2R Attacks
title_fullStr Applying Neural Network to U2R Attacks
title_full_unstemmed Applying Neural Network to U2R Attacks
title_sort applying neural network to u2r attacks
publishDate 2010
url http://eprints.utp.edu.my/3081/1/6.pdf
http://eprints.utp.edu.my/3081/
_version_ 1738655242910695424
score 13.211869

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