Motivated by the growing popularity of smart TVs, we present a large-scale measurement study of smart TVs by collecting and analyzing their network traffic from two different vantage points. First, we analyze aggregate network traffic of smart TVs in-the-wild, collected from residential gateways of tens of homes and several different smart TV platforms, including Apple, Samsung, Roku, and Chromecast. In addition to accessing video streaming and cloud services, we find that smart TVs frequently connect to well-known as well as platform-specific advertising and tracking services (ATS). Second, we instrument Roku and Amazon Fire TV, two popular smart TV platforms, by setting up a controlled testbed to systematically exercise the top-1000 apps on each platform, and analyze their network traffic at the granularity of the individual apps. We again find that smart TV apps connect to a wide range of ATS, and that the key players of the ATS ecosystems of the two platforms are different from each other and from that of the mobile platform. Third, we evaluate the (in)effectiveness of state-of-the-art DNS-based blocklists in filtering advertising and tracking traffic for smart TVs. We find that personally identifiable information (PII) is exfiltrated to platform-related Internet endpoints and third parties, and that blocklists are generally better at preventing exposure of PII to third parties than to platform-related endpoints. Our work demonstrates the segmentation of the smart TV ATS ecosystem across platforms and its differences from the mobile ATS ecosystem, thus motivating the need for designing privacy-enhancing tools specifically for each smart TV platform.
翻译:以智能电视日益受欢迎为动力,我们通过收集和分析两个不同的有利点的网络网络流量,对智能电视进行大规模计量研究。首先,我们分析从数十个住家的住宅网关和包括苹果、三星、罗库和Chromecast等数个不同的智能电视平台收集的智能电视综合网络流量。除了访问视频流和云服务外,我们发现智能电视经常与众所周知的和平台特有的广告和跟踪服务(ATS)连接。第二,我们用Roku和亚马逊火电电视,两个受欢迎的智能电视平台,通过设置一个有控制的测试台,系统运行每个平台上的1 000个顶级软件,并分析其网络流量。我们再次发现智能电视应用程序与广泛的苯丙胺类兴奋剂连接,两个平台的苯丙胺类兴奋剂生态系统的关键角色与其它不同,也与移动平台的不同。第三,我们评估了(在设计智能的DNS-S-亚马逊智能视频平台方面),每个智能智能智能视频平台需要从我们智能的智能智能视频平台到我们智能的智能视频平台。