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Fast application-level traffic classification using NetFlow records

Fast application-level traffic classification using NetFlow records

Authors :
Liang CHEN
Jian GONG
Source :
Tongxin xuebao, Vol 33, Pp 145-152 (2012)
Publication Year :
2012
Publisher :
Editorial Department of Journal on Communications, 2012.

Abstract

In order to improve the performance and reduce the resources usage of application-level traffic classification,a novel fast application-level traffic classification(FATC) algorithm using IP flow record from NetFlow as input was presented.FATC adopted metric selection algorithm based on correlation coefficient to measure the correlation among flow metric variables,and deleted the irrelevant or redundant metrics,then used Bayes discrimination to classify network traffic to the application category that of smallest misjudge loss.The theoretical analysis and experimental results show that,with more than 95% accuracy,the FATC algorithm greatl reduces the time and space complexity of current application-level traffic classification algorithms during the training and classification processes,and can work efficiently on 10Gbit/s backbone network in real time.

Details

Language :
Chinese
ISSN :
1000436X
Volume :
33
Database :
Directory of Open Access Journals
Journal :
Tongxin xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.5103330a4e94091acb0160d1b714bbd
Document Type :
article