Video Call Traffic Identification based on Bayesian Model

DOI

10.2991/icsem.2013.232How to use a DOI?

Keywords

traffic identification, VoIP, Bayesian, probability density

Abstract

This paper proposes Bayesian statistical method to identify the video traffic by the symmetrical features and coding statistical characteristics of video calls. According to the problem of high computational complexity of the non-parametric probability density estimate method in the condition of large samples, we propose grid probability density estimation method of gird division to reduce the computational complexity. We present identification results. The experimental results indicate that that this method can effectively detect video call traffic.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ying Hou
AU  - Hai Huang
AU  - Kai Wang
AU  - Yu-hang Zhu
PY  - 2013/04
DA  - 2013/04
TI  - Video Call Traffic Identification based on Bayesian Model
BT  - Proceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM 2013)
PB  - Atlantis Press
SP  - 1087
EP  - 1091
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsem.2013.232
DO  - 10.2991/icsem.2013.232
ID  - Hou2013/04
ER  -