Staff View: Impact of early estimation of statistical flow features in on-line P2P classification

Impact of early estimation of statistical flow features in on-line P2P classification

Managing high-bandwidth application traffic through identification of bandwidth-heavy Internet traffic is important for network administration. classification based on statistical flow features was proven as an encouraging method for identifying Internet traffic. Early estimation of statistical flow...

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Main Authors:	Abdalla, B. M. A., Hamdan, Mosab, Khalifa, Entisar H., Elhigazi, Abdallah, Ismail, Ismahani, Marsono, M. N.
Format:	Conference or Workshop Item
Published:	2020
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/92243/ http://dx.doi.org/10.1109/SCOReD50371.2020.9250967294299
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id	my.utm.92243
record_format	eprints
spelling	my.utm.922432021-09-28T07:34:37Z http://eprints.utm.my/id/eprint/92243/ Impact of early estimation of statistical flow features in on-line P2P classification Abdalla, B. M. A. Hamdan, Mosab Khalifa, Entisar H. Elhigazi, Abdallah Ismail, Ismahani Marsono, M. N. TK Electrical engineering. Electronics Nuclear engineering Managing high-bandwidth application traffic through identification of bandwidth-heavy Internet traffic is important for network administration. classification based on statistical flow features was proven as an encouraging method for identifying Internet traffic. Early estimation of statistical flow features from first n packets still plays an essential role in accurate and timely traffic classification. In this work, we investigate the impact of early estimation of statistical flow features for on-line P2P classification in terms of accuracy, Kappa statistic and classification time. Simulations were conducted using available traces from the University of Brescia. Results illustrate the early statistical flow features estimation for gives the most significant accuracy and efficiency to detect P2P traffic. 2020 Conference or Workshop Item PeerReviewed Abdalla, B. M. A. and Hamdan, Mosab and Khalifa, Entisar H. and Elhigazi, Abdallah and Ismail, Ismahani and Marsono, M. N. (2020) Impact of early estimation of statistical flow features in on-line P2P classification. In: 2020 IEEE Student Conference on Research and Development, SCOReD 2020, 27 - 28 September 2020, Virtual, Johor, Malaysia. http://dx.doi.org/10.1109/SCOReD50371.2020.9250967294299
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	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Abdalla, B. M. A. Hamdan, Mosab Khalifa, Entisar H. Elhigazi, Abdallah Ismail, Ismahani Marsono, M. N. Impact of early estimation of statistical flow features in on-line P2P classification
description	Managing high-bandwidth application traffic through identification of bandwidth-heavy Internet traffic is important for network administration. classification based on statistical flow features was proven as an encouraging method for identifying Internet traffic. Early estimation of statistical flow features from first n packets still plays an essential role in accurate and timely traffic classification. In this work, we investigate the impact of early estimation of statistical flow features for on-line P2P classification in terms of accuracy, Kappa statistic and classification time. Simulations were conducted using available traces from the University of Brescia. Results illustrate the early statistical flow features estimation for gives the most significant accuracy and efficiency to detect P2P traffic.
format	Conference or Workshop Item
author	Abdalla, B. M. A. Hamdan, Mosab Khalifa, Entisar H. Elhigazi, Abdallah Ismail, Ismahani Marsono, M. N.
author_facet	Abdalla, B. M. A. Hamdan, Mosab Khalifa, Entisar H. Elhigazi, Abdallah Ismail, Ismahani Marsono, M. N.
author_sort	Abdalla, B. M. A.
title	Impact of early estimation of statistical flow features in on-line P2P classification
title_short	Impact of early estimation of statistical flow features in on-line P2P classification
title_full	Impact of early estimation of statistical flow features in on-line P2P classification
title_fullStr	Impact of early estimation of statistical flow features in on-line P2P classification
title_full_unstemmed	Impact of early estimation of statistical flow features in on-line P2P classification
title_sort	impact of early estimation of statistical flow features in on-line p2p classification
publishDate	2020
url	http://eprints.utm.my/id/eprint/92243/ http://dx.doi.org/10.1109/SCOReD50371.2020.9250967294299
_version_	1712285069020758016
score	13.211869

Impact of early estimation of statistical flow features in on-line P2P classification

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