Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming

Abstract

The dynamic adaptation of the video quality induced by HTTP Adaptive Streaming (HAS) technology introduces new Quality of Experience (QoE) metrics beyond re-buffering. In this work we address the problem of real-time QoE monitoring of HAS, focusing on the continuous prediction of video resolution and average video bitrate, for the particular case of YouTube. Through empirical evaluations over a large video dataset, we demonstrate that it is possible to accurately predict the specific video resolution, as well as the average video bitrate, both in real time, and using a time granularity as small as one new prediction every second, not achieved by other proposals in the literature.