TY - GEN
T1 - Video quality representation classification of Safari encrypted DASH streams
AU - Dubin, Ran
AU - Hadar, Ofer
AU - Richman, Itai
AU - Trabelsi, Ofir
AU - Dvir, Amit
AU - Pele, Ofir
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/22
Y1 - 2016/9/22
N2 - 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 96.13% average accuracy.
AB - 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 96.13% average accuracy.
KW - Encrypted Traffic
KW - HTTPS Video Streaming
KW - Quality Representation Classification
KW - Safari
UR - http://www.scopus.com/inward/record.url?scp=84991780883&partnerID=8YFLogxK
U2 - 10.1109/DMIAF.2016.7574935
DO - 10.1109/DMIAF.2016.7574935
M3 - Conference contribution
AN - SCOPUS:84991780883
T3 - 2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Proceedings
SP - 213
EP - 216
BT - 2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers
T2 - 2016 Digital Media Industry and Academic Forum, DMIAF 2016
Y2 - 4 July 2016 through 6 July 2016
ER -