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The increasing popularity of HTTP adaptive video streaming services hasdramatically increased bandwidth requirements on operator networks, whichattempt to shape their traffic through Deep Packet Inspection (DPI). However,Google and certain content providers have started to encrypt their videoservices. As a result, operators often encounter difficulties in shaping theirencrypted video traffic via DPI. This highlights the need for new trafficclassification methods for encrypted HTTP adaptive video streaming to enablesmart traffic shaping. These new methods will have to effectively estimate thequality representation layer and playout buffer. We present a new method andshow for the first time that video quality representation classification for(YouTube) encrypted HTTP adaptive streaming is possible. We analyze theperformance of this classification method with Safari over HTTPS. Based on alarge number of offline and online traffic classification experiments, wedemonstrate that it can independently classify, in real time, every videosegment into one of the quality representation layers with 97.18% averageaccuracy.

Real Time Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming - the Case of Safari