Harvesting unique characteristics in packet sequences for effective application classification

Abstract

Network traffic classification is critical to both network management and security. Identifying application traffic at the flow level with signature matching has been widely used as the most efficient method due to its reliability and robustness. However, due to the increasing number of applications and their frequent updates, we have to constantly regenerate application signatures, which is both resource intensive and time consuming. To address this issue, we propose to explore the unique characteristics in packet sequences and discovered two types of packet sequence signatures. We introduce our design and implementation of an automated packet-sequence signature construction (APSC) system, based on association rule mining and data clustering technologies. This system can not only automatically generate traditional signatures from individual packet payloads but also construct new packet sequence signatures based on payloads or features from packet sequences, even for encrypted flows. To the best of our knowledge, this is the first practical and efficient system that supports automated packet sequence signature construction. Our experimental results show that the proposed system can automatically construct high quality signatures for a variety of application with limited overhead.

DOI: 10.1109/CNS.2013.6682724

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Cite this paper

@article{Yuan2013HarvestingUC, title={Harvesting unique characteristics in packet sequences for effective application classification}, author={Zhenlong Yuan and Yibo Xue and Yingfei Dong}, journal={2013 IEEE Conference on Communications and Network Security (CNS)}, year={2013}, pages={341-349} }