Title
Detecting VoIP Traffic Based on Human Conversation Patterns
Abstract
Owing to the enormous growth of VoIP applications, an effective means of identifying VoIP is now essential for managing a number of network traffic issues, such as reserving bandwidth for VoIP traffic, assigning high priority for VoIP flows, or blocking VoIP calls to certain destinations. Because the protocols, port numbers, and codecs used by VoIP services are shifting toward proprietary, encrypted, and dynamic methods, traditional VoIP identification approaches, including port- and payload-based schemes, are now less effective. Developing a traffic identification scheme that can work for general VoIP flows is therefore of paramount importance. In this paper, we propose a VoIP flow identification scheme based on the unique interaction pattern of human conversations . Our scheme is particularly useful for two reasons: 1) flow detection relies on human conversations rather than packet timing; thus, it is resistant to network variability; and 2) detection is based on a short sequence of voice activities rather than the whole packet stream. Hence, the scheme can operate as a traffic management module to provide QoS guarantees or block VoIP calls in real time. The performance evaluation, which is based on extensive real-life traffic traces, shows that the proposed method achieves an identification accuracy of 95% in the first 4 seconds of the detection period and 97% in 11 seconds.
Year
DOI
Venue
2008
10.1007/978-3-540-89054-6_14
IPTComm
Keywords
Field
DocType
human conversation,human conversation patterns,network traffic issue,extensive real-life traffic trace,detecting voip traffic,traffic identification scheme,voip service,traditional voip identification approach,voip traffic,general voip flow,voip flow identification scheme,voip application,voice activity detection,human speech,traffic management,real time,traffic classification,markov model
Traffic classification,Traffic generation model,Identification scheme,Computer science,Computer security,Voice activity detection,Network packet,Computer network,Quality of service,Real-time computing,Encryption,Voice over IP
Conference
Volume
ISSN
Citations 
5310
0302-9743
7
PageRank 
References 
Authors
0.51
7
4
Name
Order
Citations
PageRank
Chen-Chi Wu123817.12
Kuan-Ta Chen21896136.86
Yu-Chun Chang344825.55
Chin-Laung Lei41686201.07