An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks

An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks

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Main Author: Idris, Mohd. Yazid
Format: Thesis
Published: 2008
Subjects:
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id my-utm-ep.18720
record_format uketd_dc
spelling my-utm-ep.187202012-05-30T08:47:43Z An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks 2008 Idris, Mohd. Yazid Unspecified 2008 Thesis http://eprints.utm.my/id/eprint/18720/ 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 Unspecified
spellingShingle Unspecified
Idris, Mohd. Yazid
An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
description
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Idris, Mohd. Yazid
author_facet Idris, Mohd. Yazid
author_sort Idris, Mohd. Yazid
title An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
title_short An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
title_full An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
title_fullStr An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
title_full_unstemmed An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
title_sort efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department Faculty of Computer Science and Information System
publishDate 2008
_version_ 1747815342363639808

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