An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques

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Bibliographic Details
Main Author:	Zainal, Anazida
Format:	Thesis
Published:	2011
Subjects:	QA75 Electronic computers Computer science
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id	my-utm-ep.26406
record_format	uketd_dc
spelling	my-utm-ep.264062017-07-05T07:31:58Z An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques 2011 Zainal, Anazida QA75 Electronic computers. Computer science 2011 Thesis http://eprints.utm.my/id/eprint/26406/ http://libraryopac.utm.my/client/en_AU/main/search/results?qu=An+adaptive+intrusion+detection+model+for+dynamic+network+traffic+patterns+using+machine+learning+techniques&te= phd doctoral Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Zainal, Anazida An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
description
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Zainal, Anazida
author_facet	Zainal, Anazida
author_sort	Zainal, Anazida
title	An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
title_short	An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
title_full	An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
title_fullStr	An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
title_full_unstemmed	An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
title_sort	adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2011
_version_	1747815468679299072

An adaptive intrusion detection model for dynamic network traffic patterns using machine learning techniques

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