A FRAMEWORK FOR QOE ANALYSIS OF ENCRYPTED VIDEO
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Today most internet traffic is generated by video streaming. YouTube and other video streaming platforms are using encrypted streams (HTTPS) for transport of video content. Encryption will lead to more requirements on network and content providers, e.g. caching mechanisms will not work direct. Estimation of video quality for measuring users satisfaction is also harder because there is no direct access to the video bitstream. We are building up a framework for analyzing video quality that allows us to store client information, decrypted network traffic and encrypted messages. Our approach is based on a man-in-the-middle proxy for storing the decrypted video bitstream, active probing and traffic shaping. Using these data, we are able to calculate video QoE values for example using a model such as ITU-T Rec. P.1203. Our framework will be used for generating datasets for encrypted video stream analysis, analyzing internal behavior of video streaming platforms, and more. For experimental evaluation, in this paper we analyze the influence of our man-in-the-middle proxy on key-performance indicators (KPIs) for video streaming quality.
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