Identifying skype traffic in a large-scale flow data repository

Abstract

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. © 2011 Springer-Verlag Berlin Heidelberg.