Characterizing User Platforms for Video Streaming in Broadband Networks

被引:0
|
作者
Wang, Yifan [1 ]
Lyu, Minzhao [1 ]
Sivaraman, Vijay [1 ]
机构
[1] Univ New South Wales, Sydney, NSW, Australia
关键词
Network traffic analysis; user platform identification; video streaming; TLS fingerprinting; REAL-TIME; TRAFFIC CLASSIFICATION;
D O I
10.1145/3646547.3688435
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Internet Service Providers (ISPs) bear the brunt of being the first port of call for poor video streaming experience. ISPs can benefit from knowing the user's device type (e.g., Android, iOS) and software agent (e.g., native app, Chrome) to troubleshoot platform-specific issues, plan capacity and create custom bundles. Unfortunately, encryption and NAT have limited ISPs' visibility into user platforms across video streaming providers. We develop a methodology to identify user platforms for video streams from four popular providers, namely YouTube, Netflix, Disney, and Amazon, by analyzing network traffic in real-time. First, we study the anatomy of the connection establishment process to show how TCP/QUIC and TLS handshakes vary across user platforms. We then develop a classification pipeline that uses 62 attributes extracted from the handshake messages to determine the user device and software agent of video flows with over 96% accuracy. Our method is evaluated and deployed in a large campus network (mimicking a residential broadband network) serving users including dormitory residents. Analysis of 100+ million video streams over a four-month period reveals insights into the mix of user platforms across the video providers, variations in bandwidth consumption across operating systems and browsers, and differences in peak hours of usage.
引用
收藏
页码:563 / 579
页数:17
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