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.
Though it is commonly assumed that Internet traffic is dominated by TCP, there has been an increasing demand for UDP based P2P applications. UDP is widely used in new P2P networks because it can provides better support for NAT traversal. Since many of these applications use private protocols, UDP traffic is often hard to analyze, especially if the available data is only netflow records. In this paper, a component based method is proposed to analyze UDP traffic. Since flows in each component share the same application, P2P traffic can be identified without packet level information.
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