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Motivated by the growing popularity of smart TVs, we present a large-scalemeasurement study of smart TVs by collecting and analyzing their networktraffic from two different vantage points. First, we analyze aggregate networktraffic of smart TVs in-the-wild, collected from residential gateways of tensof homes and several different smart TV platforms, including Apple, Samsung,Roku, and Chromecast. In addition to accessing video streaming and cloudservices, we find that smart TVs frequently connect to well-known as well asplatform-specific advertising and tracking services (ATS). Second, weinstrument Roku and Amazon Fire TV, two popular smart TV platforms, by settingup a controlled testbed to systematically exercise the top-1000 apps on eachplatform, and analyze their network traffic at the granularity of theindividual apps. We again find that smart TV apps connect to a wide range ofATS, and that the key players of the ATS ecosystems of the two platforms aredifferent from each other and from that of the mobile platform. Third, weevaluate the (in)effectiveness of state-of-the-art DNS-based blocklists infiltering advertising and tracking traffic for smart TVs. We find thatpersonally identifiable information (PII) is exfiltrated to platform-relatedInternet endpoints and third parties, and that blocklists are generally betterat preventing exposure of PII to third parties than to platform-relatedendpoints. Our work demonstrates the segmentation of the smart TV ATS ecosystemacross platforms and its differences from the mobile ATS ecosystem, thusmotivating the need for designing privacy-enhancing tools specifically for eachsmart TV platform.

The TV is Smart and Full of Trackers: Towards Understanding the Smart TV Advertising and Tracking Ecosystem