使用最大可分辨端口的UDP流分类

Qianli Zhang, Yunlong Ma, Jilong Wang, Xing Li
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引用次数: 10

摘要

与TCP流量相比,UDP流量的构成还不清楚。尽管观察到很大一部分UDP流量似乎是P2P应用程序,但应用程序级别的UDP流量分类仍然非常困难,因为大多数这些应用程序都是基于私有协议的。本文提出了一种新的UDP流量分类方法。基于来自两个通信半元组的流量来自同一应用程序的假设,所有半元组都可以分组到几个连接的子图中。因此,每个子组中大多数链路或半元组所采用的端口号可以用来表征整个子组的应用类型。实验结果表明,该方法是可行的,可以仅利用流级信息对UDP流量进行分类。大多数链接或半元组所采用的端口号在不同时间段之间的稳定性令人惊讶,例如优酷应用程序在1429个时间段中有90%以上的时间段保持不变。
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UDP traffic classification using most distinguished port
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.
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