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:
Online Access:http://eprints.utm.my/id/eprint/18720/
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Institution: Universiti Teknologi Malaysia
id my.utm.18720
record_format eprints
spelling my.utm.187202012-05-30T08:47:43Z http://eprints.utm.my/id/eprint/18720/ An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks Idris, Mohd. Yazid Unspecified 2008 Thesis NonPeerReviewed Idris, Mohd. Yazid (2008) An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks. PhD thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Unspecified
spellingShingle Unspecified
Idris, Mohd. Yazid
An efficient on - line hurst parameter estimator for detecting volume - based network intrusion attacks
format Thesis
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
publishDate 2008
url http://eprints.utm.my/id/eprint/18720/
_version_ 1643646981055184896