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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Main Author: Mohamad, Shamsul
Format: Thesis
Language:English
Published: 2003
Subjects:
Online Access:http://eprints.uthm.edu.my/8240/1/24p%20SHAMSUL%20MOHAMAD.pdf
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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