Data mining in network traffic using fuzzy clustering

Nowadays, in network traffic, we have various application such as HfTP, Telnet, SMTP, FTP and NetBIOS. These various application make it difficult for the network administrator to model certain network traffic. The network traffic model is very important to know whether that particular network t...

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Bibliographic Details
Main Author:	Mohamad, Shamsul
Format:	Thesis
Language:	English
Published:	2003
Subjects:	QA Mathematics QA71-90 Instruments and machines
Online Access:	http://eprints.uthm.edu.my/8240/1/24p%20SHAMSUL%20MOHAMAD.pdf
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id	my-uthm-ep.8240
record_format	uketd_dc
spelling	my-uthm-ep.82402023-02-07T03:35:48Z Data mining in network traffic using fuzzy clustering 2003-12 Mohamad, Shamsul QA Mathematics QA71-90 Instruments and machines Nowadays, in network traffic, we have various application such as HfTP, Telnet, SMTP, FTP and NetBIOS. These various application make it difficult for the network administrator to model certain network traffic. The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. The fuzzy clustering process are made using three algorithms : Fuzzy C-Means (FCM), Gustafsof-Kessel (GK) and Gath-Geva (GG) algorithm. The production of clustering are used to build rules. 2003-12 Thesis http://eprints.uthm.edu.my/8240/ http://eprints.uthm.edu.my/8240/1/24p%20SHAMSUL%20MOHAMAD.pdf text en public mphil masters Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English
topic	QA Mathematics QA71-90 Instruments and machines
spellingShingle	QA Mathematics QA71-90 Instruments and machines Mohamad, Shamsul Data mining in network traffic using fuzzy clustering
description	Nowadays, in network traffic, we have various application such as HfTP, Telnet, SMTP, FTP and NetBIOS. These various application make it difficult for the network administrator to model certain network traffic. The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. The fuzzy clustering process are made using three algorithms : Fuzzy C-Means (FCM), Gustafsof-Kessel (GK) and Gath-Geva (GG) algorithm. The production of clustering are used to build rules.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohamad, Shamsul
author_facet	Mohamad, Shamsul
author_sort	Mohamad, Shamsul
title	Data mining in network traffic using fuzzy clustering
title_short	Data mining in network traffic using fuzzy clustering
title_full	Data mining in network traffic using fuzzy clustering
title_fullStr	Data mining in network traffic using fuzzy clustering
title_full_unstemmed	Data mining in network traffic using fuzzy clustering
title_sort	data mining in network traffic using fuzzy clustering
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2003
url	http://eprints.uthm.edu.my/8240/1/24p%20SHAMSUL%20MOHAMAD.pdf
_version_	1776103309050904576

Data mining in network traffic using fuzzy clustering

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