What TCP/IP protocol headers can tell us about the web
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Analyzing peer-to-peer traffic across large networks
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
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
An analysis of internet content delivery systems
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Identification and Analysis of P2P Traffic- An Example of BitTorrent
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2
Rarest first and choke algorithms are enough
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Finding peer-to-peer file-sharing using coarse network behaviors
ESORICS'06 Proceedings of the 11th European conference on Research in Computer Security
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Bittorrent is currently one of the most popular peer-to-peer (P2P) file sharing protocols. However, it incurs such excessive amount of traffic that it may adversely affect users of legacy internet applications. To limit this adverse impact, an efficient methodology for bittorrent identification may be needed. In this paper, we propose a novel approach to identify local bittorrent peers. Our approach is based on behaviors of the choke algorithm, a main algorithm used in bittorrent. An advantage of our approach is that we can identify bittorrent peers without examining the packet pay-load. Therefore, our approach is free from privacy issues and still effective even though the packet payload is encrypted. Unlike previous works, we identify bittorrent hosts at the peer level instead of the flow level. Given that we use only information from network layer instead of transport layer, our work maintains fewer states and achieves robustness to changes in the transport layer. Furthermore, our work is effective even in restricted environments such as networks equipped with NAT devices or firewalls without modifications to existing network equipments. Our experimental result indicates that our approach can efficiently identify most of excessive bandwidth-consuming peers (i.e., peers transfer a large amount of data in our traces) with a low false-positive rate.