Title :
Differentiating voice and data traffic using statistical properties
Author :
Buyukkayhan, Ahmet S. ; Kavak, A. ; Yaprak, Ece
Author_Institution :
Dept. of Comput. Eng., Yeditepe Univ., Istanbul, Turkey
Abstract :
In this paper, we determine the statistical properties of the Real Time Protocol (RTP) flows and enhance the Statistical Protocol Identification (SPID) application to differentiate voice and data traffic. We added 3 new attribute meters and generate a model database for the Session Initiation Protocol (SIP) and RTP protocols. The preliminary results with very low number of training capture seem promising. The results show that our new attributes improve the RTP flow identification recall by 15%.
Keywords :
signalling protocols; statistical analysis; RTP flow identification recall; RTP protocols; SIP; SPID; data traffic; real time protocol; session initiation protocol; statistical properties; statistical protocol identification; voice traffic; Computers; Databases; Ports (Computers); Protocols; Radiation detectors; Training; Vectors; Packet classification; QoS; RTP; Traffic classification; VoIP;
Conference_Titel :
Electronics, Computer and Computation (ICECCO), 2013 International Conference on
Conference_Location :
Ankara
DOI :
10.1109/ICECCO.2013.6718232
