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A Longitudinal Study of P2P Traffic Classification
Abstract
This paper focuses on network traffic measurement of Peer-to- Peer (P2P) applications on the Internet. P2P applications supposedly constitute a substantial proportion of today's Internet traffic. However, current P2P applications use several obfuscation techniques, including dynamic port numbers, port hopping, HTTP masquerading, chunked file transfers, and encrypted payloads. As P2P applications continue to evolve, robust and effective methods are needed for P2P traffic identification. The paper compares three methods to classify P2P applications: port-based classification, application-layer signatures, and transport-layer analysis. The study uses empirical network traces collected from the University of Calgary Internet connection for the past 2 years. The results show that port-based analysis is ineffective, being unable to identify 30%-70% of today's Internet traffic. Application signatures are accurate, but may not be possible for legal or technical reasons. The transport-layer method seems promising, providing a robust means to assess aggregate P2P traffic. The latter method suggests that 30%-70% of the campus Internet traffic for the past year was P2P.
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Cited by
A survey of techniques for internet traffic classification using machine learning
Nguyen, T. T. T., & Armitage, G. (2008) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2008.080406 · Cited by 1,664
Deep packet: a novel approach for encrypted traffic classification using deep learning
Lotfollahi, M., Jafari Siavoshani, M., Shirali Hossein Zade, R., & Saberian, M. (2020) · Soft Computing · doi:10.1007/s00500-019-04030-2 · Cited by 1,190
Silva, S. S. C., Silva, R. M. P., Pinto, R. C. G., & Salles, R. M. (2013) · Computer Networks · doi:10.1016/j.comnet.2012.07.021 · Cited by 356
Lin, K., Xu, X., & Gao, H. (2021) · Computer Networks · doi:10.1016/j.comnet.2021.107974 · Cited by 226
Identifying and discriminating between web and peer-to-peer traffic in the network core
Erman, J., Mahanti, A., Arlitt, M., & Williamson, C. (2007) · Proceedings of the 16th international conference on World Wide Web · doi:10.1145/1242572.1242692 · Cited by 213
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Metadata
- Authors
- Madhukar, A., & Williamson, C.
- Venue
- 14th IEEE International Symposium on Modeling, Analysis, and Simulation
- Publisher
- IEEE
- Published
- 2006-10-24
- Pages
- 179-188
- OpenAlex
- W1495633614
- Cited by
- 247
- References
- 0
- FWCI
- 8.64
- Type
- conference paper
- Language
- en
- Open access
- closed
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