Revealing skype traffic: when randomness plays with you
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
A Preliminary Investigation of Skype Traffic Classification Using a Minimalist Feature Set
ARES '08 Proceedings of the 2008 Third International Conference on Availability, Reliability and Security
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Real-Time Algorithm for Skype Traffic Detection and Classification
NEW2AN '09 and ruSMART '09 Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces
Detailed analysis of Skype traffic
IEEE Transactions on Multimedia
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
LISA'10 Proceedings of the 24th international conference on Large installation system administration
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We present a novel method for identifying Skype clients and supernodes on a network using only flow data, based upon the detection of certain Skype control traffic. Flow-level identification allows long-term retrospective studies of Skype traffic as well as studies of Skype traffic on much larger scale networks than existing packet-based approaches. We use this method to identify Skype hosts and connection events to the network in a historical flow data set containing 182 full days of data over the six years from 2004 to 2009, in order to explore the evolution of the Skype network in general and a large observed portion thereof in particular. This represents, to the best of our knowledge, the first long-term retrospective analysis of the behavior of the Skype network based solely on flow data, and the first successful application of a Skype detection algorithm to flow data collected from a production network.