Performance of packet filtering using back propagation algorithm

In this paper we analyzed the use of neural network for packet filtering. The neural network system was designed in eight ways with input to the neural network in the form of either access rules or optimized access rules or binary form of access rules or representing wildcards as 0 & 255 or c...

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Main Authors: M.I.Buhari,, M. H. Habaebi,, Burhanuddin Mohd.Ali,
Format: Article
Published: 2004
Online Access:http://journalarticle.ukm.my/1426/
http://www.ukm.my/jkukm/index.php/jkukm
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spelling my-ukm.journal.14262011-10-11T03:45:18Z http://journalarticle.ukm.my/1426/ Performance of packet filtering using back propagation algorithm M.I.Buhari, M. H. Habaebi, Burhanuddin Mohd.Ali, In this paper we analyzed the use of neural network for packet filtering. The neural network system was designed in eight ways with input to the neural network in the form of either access rules or optimized access rules or binary form of access rules or representing wildcards as 0 & 255 or combination of them. These trained neural networks were analyzed for their correctness and the performance aspects such as training time using test data. In order to further improve the security, the data related to the local usage of the network were also used to train the network. An example of implementing these trained systems in active networks packet filtering was presented 2004 Article PeerReviewed M.I.Buhari, and M. H. Habaebi, and Burhanuddin Mohd.Ali, (2004) Performance of packet filtering using back propagation algorithm. Jurnal Kejuruteraan, 16 . http://www.ukm.my/jkukm/index.php/jkukm
institution Universiti Kebangsaan Malaysia
building Perpustakaan Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
description In this paper we analyzed the use of neural network for packet filtering. The neural network system was designed in eight ways with input to the neural network in the form of either access rules or optimized access rules or binary form of access rules or representing wildcards as 0 & 255 or combination of them. These trained neural networks were analyzed for their correctness and the performance aspects such as training time using test data. In order to further improve the security, the data related to the local usage of the network were also used to train the network. An example of implementing these trained systems in active networks packet filtering was presented
format Article
author M.I.Buhari,
M. H. Habaebi,
Burhanuddin Mohd.Ali,
spellingShingle M.I.Buhari,
M. H. Habaebi,
Burhanuddin Mohd.Ali,
Performance of packet filtering using back propagation algorithm
author_facet M.I.Buhari,
M. H. Habaebi,
Burhanuddin Mohd.Ali,
author_sort M.I.Buhari,
title Performance of packet filtering using back propagation algorithm
title_short Performance of packet filtering using back propagation algorithm
title_full Performance of packet filtering using back propagation algorithm
title_fullStr Performance of packet filtering using back propagation algorithm
title_full_unstemmed Performance of packet filtering using back propagation algorithm
title_sort performance of packet filtering using back propagation algorithm
publishDate 2004
url http://journalarticle.ukm.my/1426/
http://www.ukm.my/jkukm/index.php/jkukm
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score 13.211869