CSI: inferring mobile ABR video adaptation behavior under HTTPS and QUIC

Mobile video streaming services have widely adopted Adaptive Bitrate (ABR) streaming to dynamically adapt the streaming quality to variable network conditions. A wide range of third-party entities such as network providers and testing services need to understand such adaptation behavior for purposes such as QoE monitoring and network management. The traditional approach involved conducting test runs and analyzing the HTTP-level information from the associated network traffic to understand the adaptation behavior under different network conditions. However, end-to-end traffic encryption protocols such as HTTPS and QUIC are being increasingly used by streaming services, hindering such traditional traffic analysis approaches.

To address this, we develop CSI (Chunk Sequence Inferencer), a general system that enables third-parties to conduct active measurements and infer mobile ABR video adaptation behavior based on packet size and timing information still available in the encrypted traffic. We perform extensive evaluations and demonstrate that CSI achieves high inference accuracy for video encodings of popular streaming services covering various ABR system designs. As an illustration, for a popular mobile video service, we show that CSI can effectively help understand the video QoE implications of network traffic shaping policies and develop optimized policies, even in the presence of encryption.