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Mar. 4, 2008 to Mar. 7, 2008
ISBN: 978-0-7695-3102-1
pp: 1075-1079
ABSTRACT
In this work, AdaBoost and C4.5, are employed for classifying Skype direct (UDP and TCP) communications from traffic log files. Pre-processing is applied to the traffic data to express it as flows, which is later converted into a descriptive feature set. The aforementioned algorithms are then evaluated on this feature set. Results show that a 98% detection rate with6% false positive rate for UDP based Skype and a 94% detection rate with 4% false positive rate for TCP based Skype is possible to achieve.
INDEX TERMS
traffic classification, skype, encrypted
CITATION
Duffy Angevine, Nur Zincir-Heywood, "A Preliminary Investigation of Skype Traffic Classification Using a Minimalist Feature Set", ARES, 2008, 2012 Seventh International Conference on Availability, Reliability and Security, 2012 Seventh International Conference on Availability, Reliability and Security 2008, pp. 1075-1079, doi:10.1109/ARES.2008.158
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