  The increasing popularity of HTTP adaptive video streaming services has
dramatically increased bandwidth requirements on operator networks, which
attempt to shape their traffic through Deep Packet Inspection (DPI). However,
Google and certain content providers have started to encrypt their video
services. As a result, operators often encounter difficulties in shaping their
encrypted video traffic via DPI. This highlights the need for new traffic
classification methods for encrypted HTTP adaptive video streaming to enable
smart traffic shaping. These new methods will have to effectively estimate the
quality representation layer and playout buffer. We present a new method and
show for the first time that video quality representation classification for
(YouTube) encrypted HTTP adaptive streaming is possible. We analyze the
performance of this classification method with Safari over HTTPS. Based on a
large number of offline and online traffic classification experiments, we
demonstrate that it can independently classify, in real time, every video
segment into one of the quality representation layers with 97.18% average
accuracy.
