Measuring IP and TCP behavior on edge nodes with Tstat
Computer Networks: The International Journal of Computer and Telecommunications Networking
Revealing skype traffic: when randomness plays with you
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Live traffic monitoring with tstat: capabilities and experiences
WWIC'10 Proceedings of the 8th international conference on Wired/Wireless Internet Communications
Wire-speed statistical classification of network traffic on commodity hardware
Proceedings of the 2012 ACM conference on Internet measurement conference
Characterizing per-application network traffic using entropy
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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This paper focuses on the characterization and classification of Skype traffic, a nowadays very popular and fashionable VoIP application. Building over previous work, we develop a software tool which can be used to examine the evolution of Skype call classification in an interactive fashion. The demonstrator software focuses on the main aspects of Skype traffic characterization and presents the traffic patterns Skype generates during a call or while idle. In addition, the demonstrator shows the evolution of the internal indexes the Skype classifiers use. After describing the classification process and the demonstrator software, we use the tool to demonstrate the feasibility of online Skype traffic identification, considering both accuracy and computational costs. Experimental results show that few seconds of observation are enough to allow the classifier engines to correctly identify the presence of Skype flows. Moreover, results indicate that the classification engine can cope with multi-Gbps links in real-time using common off-the-shelf hardware.