A low-bandwidth network file system
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Accurate, scalable in-network identification of p2p traffic using application signatures
Proceedings of the 13th international conference on World Wide Web
Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
ACAS: automated construction of application signatures
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
ACM SIGCOMM Computer Communication Review
Comprehensive view of a live network coding P2P system
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Unexpected means of protocol inference
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Autograph: toward automated, distributed worm signature detection
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Semi-supervised network traffic classification
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
ACM SIGCOMM Computer Communication Review
Revealing skype traffic: when randomness plays with you
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Toward the accurate identification of network applications
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
Self-Learning IP traffic classification based on statistical flow characteristics
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
Network traffic classification via HMM under the guidance of syntactic structure
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Classifying network traffic according to its applications is important to a broad range of network areas. Since new applications, especially P2P applications, no longer use well-known fixed port numbers, the native port based traffic classification technique has become much less effective. In this paper, we propose a novel approach to identify P2P traffic by leveraging on the data transfer behaviour of P2P applications. The behaviour investigated in the paper is that downloaded data from a P2P host will be uploaded to other hosts later. To find the shared data of downloading flows and uploading flows online, the content based partitioning schema is used to partition the flows into data blocks. Flows sharing the same data blocks are identified as P2P flows. The effectiveness of this method is demonstrated by experiments on various P2P applications. The results show that the algorithm can identify P2P applications very accurately while only keeping a small set of data blocks. The method is generic and can be applied to most P2P applications.