DocumentCode :
1781134
Title :
UDP traffic classification using most distinguished port
Author :
Qianli Zhang ; Yunlong Ma ; Jilong Wang ; Xing Li
Author_Institution :
CERNET Center, Tsinghua Univ., Beijing, China
fYear :
2014
fDate :
17-19 Sept. 2014
Firstpage :
1
Lastpage :
4
Abstract :
Comparing to TCP traffic, the composition of UDP traffic is still unclear. Although it is observed that a large fraction of UDP traffic appears to be P2P applications, application level classification of UDP traffic is still very hard since most of these applications are private protocols based. In this paper, a novel method is proposed to classify UDP traffic. Based on the assumption that traffic from two communicating half-tuples identified by the <; IP address, portnumber > is from the same application, all half-tuples can be grouped into several connected subgraphs. The port numbers which are adopted by most links or half-tuples in each subgroup can thus be used to characterize the application types of the whole subgroup. Experiment results show that this approach is feasible and can classify UDP traffic only using flow level information. The port numbers adopted by most links or half-tuples are surprisingly stable among different time periods, for example, for Youku application remain the same for more than 90% of periods in all the 1429 periods.
Keywords :
Internet; graph theory; pattern classification; peer-to-peer computing; telecommunication traffic; transport protocols; IP address; P2P applications; UDP traffic classification; UDP traffic composition; Youku application; application level classification; communicating half-tuples; connected subgraphs; flow level information; most distinguished port; port number; private protocols; Educational institutions; IP networks; Inspection; Internet; Monitoring; Ports (Computers); Protocols;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Network Operations and Management Symposium (APNOMS), 2014 16th Asia-Pacific
Conference_Location :
Hsinchu
Type :
conf
DOI :
10.1109/APNOMS.2014.6996569
Filename :
6996569
Link To Document :
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