Title :
Identifying Skype Traffic by Random Forest
Author :
Li Jun ; Zhang Shunyi ; Xuan Ye ; Sun Yanfei
Author_Institution :
Nanjing Univ. of Posts & Telecommun., Nanjing
Abstract :
Despite of the great popularity, little is known about Skype network attributed to proprietary protocol. End-to-end encryption disables the traditional traffic detection methods. We presented genetic algorithm based Random Forest algorithm to identify Skype traffic using only transport layer statistics. Experimental results show that the proposed approach can immune to the encryption of the payload and be capable of detecting Skype traffic with accuracy over 95% while low computational complexity is required.
Keywords :
Internet telephony; cryptography; genetic algorithms; peer-to-peer computing; telephone traffic; Random Forest algorithm; Skype traffic; computational complexity; end-to-end encryption; genetic algorithm; transport layer statistics; Biological cells; Computational complexity; Cryptography; Genetic algorithms; Machine learning; Payloads; Radiofrequency identification; Support vector machine classification; Support vector machines; Telecommunication traffic;
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1311-9
DOI :
10.1109/WICOM.2007.705