Abstract
Different from traditional P2P traffic identification methods based on keywords or well-known ports, this paper presents a new identification method of P2P traffic based on the most basic characteristics of P2P protocol. We compare and analyze P2P traffic and traditional C/S traffic using statistical analysis techniques, and obtain two statistical characteristics of P2P traffic: continuity and multi-connectivity. In addition, the mechanism of sliding window is introduced in the quantification of the statistical characteristics to establish a P2P traffic identification model. Finally, we develop a P2P traffic identification emulation system based on the proposed model, and the experiment results reveal that this new model can identify known and unknown P2P traffic effectively.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (No. 61373135, No. 61672299).
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Hu, B., Sun, Z. (2017). P2P Traffic Identification Method Based on Traffic Statistical Characteristics. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_24
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DOI: https://doi.org/10.1007/978-3-319-63309-1_24
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