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UDP traffic classification using most distinguished port

机译:使用最杰出端口的UDP流量分类

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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.
机译:与TCP流量相比,UDP流量的组成仍然不清楚。尽管观察到很大一部分UDP流量似乎是P2P应用程序,但由于大多数这些应用程序都是基于私有协议的,因此UDP流量的应用程序级别分类仍然非常困难。本文提出了一种对UDP流量进行分类的新方法。基于以下假设:来自两个通信半元组的流量由<;标识。 IP地址,端口号>来自同一应用程序,所有半元组都可以分组为几个连接的子图。每个子组中大多数链接或半元组采用的端口号因此可以用来表征整个子组的应用程序类型。实验结果表明,该方法是可行的,只能使用流级别信息对UDP流量进行分类。大多数链接或半元组采用的端口号在不同时间段内都出乎意料地稳定,例如,对于优酷应用程序,在所有1429个时间段中,超过90%的时间段保持不变。

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