Video Call Traffic Identification Based on Bayesian Model

Ying Hou; Hai Huang; Kai Wang; Yu Hang  Zhu

doi:10.4028/www.scientific.net/AMR.765-767.1307

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767Video Call Traffic Identification Based on...

Video Call Traffic Identification Based on Bayesian Model

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.

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Periodical:

Advanced Materials Research (Volumes 765-767)

Pages:

1307-1311

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.1307

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Online since:

September 2013

Authors:

Ying Hou, Hai Huang, Kai Wang, Yu Hang Zhu

Keywords:

Bayesian, Probability Density, Traffic Identification, VOIP

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References

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