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...

Full description

Bibliographic Details
Main Author: Mohamad, Shamsul
Format: Thesis
Language:English
Published: 2003
Subjects:
Online Access:http://eprints.uthm.edu.my/8630/
http://eprints.uthm.edu.my/8630/1/24p%20SHAMSUL%20MOHAMAD.pdf
_version_ 1848889454073217024
author Mohamad, Shamsul
author_facet Mohamad, Shamsul
author_sort Mohamad, Shamsul
building UTHM Institutional Repository
collection Online Access
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.
first_indexed 2025-11-15T20:26:26Z
format Thesis
id uthm-8630
institution Universiti Tun Hussein Onn Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T20:26:26Z
publishDate 2003
recordtype eprints
repository_type Digital Repository
spelling uthm-86302023-05-02T02:11:54Z http://eprints.uthm.edu.my/8630/ Data mining in network traffic using fuzzy clustering Mohamad, Shamsul QA Mathematics QA76 Computer software 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. 2003-10 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/8630/1/24p%20SHAMSUL%20MOHAMAD.pdf Mohamad, Shamsul (2003) Data mining in network traffic using fuzzy clustering. Masters thesis, Universiti Sains Malaysia.
spellingShingle QA Mathematics
QA76 Computer software
Mohamad, Shamsul
Data mining in network traffic using fuzzy clustering
title 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_short Data mining in network traffic using fuzzy clustering
title_sort data mining in network traffic using fuzzy clustering
topic QA Mathematics
QA76 Computer software
url http://eprints.uthm.edu.my/8630/
http://eprints.uthm.edu.my/8630/1/24p%20SHAMSUL%20MOHAMAD.pdf