Evaluating Application?Layer Classification Using a Machine Learning Technique Over Different High Speed Networks

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Evaluating Application?Layer Classification Using a Machine Learning Technique Over Different High Speed Networks

Popis výsledku v původním jazyce

Classification based on machine learning offers an alternative method to methods based on port or payload based techniques. It is based on statistical features computed from network flows. Several works investigated the efficiency of machine learning techniques and found algorithms suitable for network classification. A classifier based on machine learning is built by learning from a training data set that consists of data from known application traces. In this paper, we evaluate the efficiency of application-layer classification based on C4.5 machine learning algorithm used for classification network flows from different high speed networks, such as 100 Mbit, 1 Gbit and 10 Gbit networks. We find a significant decrease in the classification efficiencywhen classifier built for one network is used to classify other network. We recommend to build classifier from data collected from all available networks for best results. Howeve

Název v anglickém jazyce

Evaluating Application?Layer Classification Using a Machine Learning Technique Over Different High Speed Networks

Popis výsledku anglicky

Classification based on machine learning offers an alternative method to methods based on port or payload based techniques. It is based on statistical features computed from network flows. Several works investigated the efficiency of machine learning techniques and found algorithms suitable for network classification. A classifier based on machine learning is built by learning from a training data set that consists of data from known application traces. In this paper, we evaluate the efficiency of application-layer classification based on C4.5 machine learning algorithm used for classification network flows from different high speed networks, such as 100 Mbit, 1 Gbit and 10 Gbit networks. We find a significant decrease in the classification efficiencywhen classifier built for one network is used to classify other network. We recommend to build classifier from data collected from all available networks for best results. Howeve

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ICSNC 2010 - The Fifth International Conference on Systems and Networks Communications

ISBN

978-0-7695-4145-7

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

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Název nakladatele

IEEE Computer Society Press

Místo vydání

Nice

Místo konání akce

Nice

Datum konání akce

22. 8. 2010

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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