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Towards real-time processing for application identification of encrypted traffic

机译:走向实时处理以识别加密流量的应用程序

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摘要

Application identification in the middle is one of key challenges for network operators to manage application based traffic and policy controls in the Internet. However, it is becoming harder according to the increase of end-to-end encrypted traffic in which we hardly read application specific information from packets. We previously proposed a method to identify the application of traffic whenever the traffic is encrypted or not. Our method gives a significant accuracy of identification of encrypted traffic as high as the case when traffic is not encrypted, however, it requires an offline processing to obtain statistics of the whole of flows. A real-time identification is important, but the accuracy is a problem due to unstable information of flow statistics. In this paper we therefore propose an approach to improve the accuracy of identification when we identify the encrypted traffic in real-time. We first clarify the sufficient number of packets required for accurate identification, and then the method to infer the statistics to improve the accuracy even when the obtained number of packets is smaller than the one required. Experimental results have shown that the proposed approach achieves the high accuracy almost the same as in offline method.
机译:中间的应用程序标识是网络运营商在Internet中管理基于应用程序的流量和策略控制的主要挑战之一。但是,随着端到端加密流量的增加,这种情况变得越来越困难,在这种情况下,我们几乎无法从数据包中读取应用程序特定的信息。我们先前提出了一种方法,无论流量是否经过加密,都可以识别流量的应用。与未加密流量的情况一样,我们的方法具有很高的识别加密流量的准确度,但是,它需要脱机处理才能获得整个流量的统计信息。实时识别很重要,但是由于流量统计信息不稳定,准确性是一个问题。因此,在本文中,我们提出了一种在实时识别加密流量时提高识别准确性的方法。我们首先阐明准确识别所需的足够数量的数据包,然后,即使所获得的数据包数量小于所需数量,也可以通过推断统计信息的方法来提高准确性。实验结果表明,所提出的方法与离线方法几乎达到了相同的精度。

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