TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming |
| 영문제목(English Title) |
Video Quality Representation Classification of Encrypted HTTP Adaptive Video Streaming |
| 저자(Author) |
Ran Dubin
Ofer Hadar
Amit Dvir
Ofir Pele
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| 원문수록처(Citation) |
VOL 12 NO. 08 PP. 3804 ~ 3819 (2018. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
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 machine learning method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. The crawler codes and the datasets are provided in [43,44,51]. An extensive empirical evaluation shows that our method is able to independently classify every video segment into one of the quality representation layers with 97% accuracy if the browser is Safari with a Flash Player and 77% accuracy if the browser is Chrome, Explorer, Firefox or Safari with an HTML5 player.
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| 키워드(Keyword) |
Machine Learning
Quality Representation Classification
HTTPS Video Streaming
Encrypted Traffic
YouTube
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| 파일첨부 |
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