2008 Third International Conference on Availability, Reliability and Security (2008)
Mar. 4, 2008 to Mar. 7, 2008
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ARES.2008.158
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.
traffic classification, skype, encrypted
D. Angevine and N. Zincir-Heywood, "A Preliminary Investigation of Skype Traffic Classification Using a Minimalist Feature Set," 2008 Third International Conference on Availability, Reliability and Security(ARES), vol. 00, no. , pp. 1075-1079, 2008.