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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F10%3A00006953" target="_blank" >RIV/63839172:_____/10:00006953 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Evaluating Application?Layer Classification Using a Machine Learning Technique Over Different High Speed Networks
Original language description
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
Czech name
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Czech description
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Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
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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Number of pages
5
Pages from-to
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Publisher name
IEEE Computer Society Press
Place of publication
Nice
Event location
Nice
Event date
Aug 22, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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