Work

Video Call Traffic Identification based on Bayesian Model

Year: 2013

Type: conference-paper

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.

Source: Proceedings of the 2nd International Conference On Systems Engineering and Modeling

DOI: 10.2991/icsem.2013.232

Authors: Ying Hou, Hai Huang, Kai Wang, Yu-hang Zhu

Institution: PLA Information Engineering University

Language: English

Topic: Internet Traffic Analysis and Secure E-voting

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National High-tech Research and Development Program

OpenAlex ID: W4232615024