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Watching TV with the Second-Party: A First Look at Automatic Content Recognition Tracking in Smart TVs

Gianluca Anselmi, Yash Vekaria, Alexander D'Souza, Patricia Callejo, Anna Maria Mandalari, Zubair Shafiq

TL;DR

A black-box audit of ACR network traffic between ACR clients on the smart TV and ACR servers is conducted to systematically investigate whether ACR tracking is agnostic to how a user watches TV, and whether there are any differences in ACR tracking between the UK and the US.

Abstract

Smart TVs implement a unique tracking approach called Automatic Content Recognition (ACR) to profile viewing activity of their users. ACR is a Shazam-like technology that works by periodically capturing the content displayed on a TV's screen and matching it against a content library to detect what content is being displayed at any given point in time. While prior research has investigated third-party tracking in the smart TV ecosystem, it has not looked into second-party ACR tracking that is directly conducted by the smart TV platform. In this work, we conduct a black-box audit of ACR network traffic between ACR clients on the smart TV and ACR servers. We use our auditing approach to systematically investigate whether (1) ACR tracking is agnostic to how a user watches TV (e.g., linear vs. streaming vs. HDMI), (2) privacy controls offered by smart TVs have an impact on ACR tracking, and (3) there are any differences in ACR tracking between the UK and the US. We perform a series of experiments on two major smart TV platforms: Samsung and LG. Our results show that ACR works even when the smart TV is used as a "dumb" external display, opting-out stops network traffic to ACR servers, and there are differences in how ACR works across the UK and the US.

Watching TV with the Second-Party: A First Look at Automatic Content Recognition Tracking in Smart TVs

TL;DR

A black-box audit of ACR network traffic between ACR clients on the smart TV and ACR servers is conducted to systematically investigate whether ACR tracking is agnostic to how a user watches TV, and whether there are any differences in ACR tracking between the UK and the US.

Abstract

Smart TVs implement a unique tracking approach called Automatic Content Recognition (ACR) to profile viewing activity of their users. ACR is a Shazam-like technology that works by periodically capturing the content displayed on a TV's screen and matching it against a content library to detect what content is being displayed at any given point in time. While prior research has investigated third-party tracking in the smart TV ecosystem, it has not looked into second-party ACR tracking that is directly conducted by the smart TV platform. In this work, we conduct a black-box audit of ACR network traffic between ACR clients on the smart TV and ACR servers. We use our auditing approach to systematically investigate whether (1) ACR tracking is agnostic to how a user watches TV (e.g., linear vs. streaming vs. HDMI), (2) privacy controls offered by smart TVs have an impact on ACR tracking, and (3) there are any differences in ACR tracking between the UK and the US. We perform a series of experiments on two major smart TV platforms: Samsung and LG. Our results show that ACR works even when the smart TV is used as a "dumb" external display, opting-out stops network traffic to ACR servers, and there are differences in how ACR works across the UK and the US.
Paper Structure (14 sections, 11 figures, 5 tables)

This paper contains 14 sections, 11 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Background and Motivation
  3. Design & Methodology
  4. Design
  5. Methodology
  6. Results
  7. Comparison Across Scenarios
  8. Comparison Across Phases
  9. Comparison Across Countries
  10. Related Work
  11. Conclusion
  12. Ethics
  13. Opt-Out Options
  14. Amount of Bytes Towards ACR Domains

Figures (11)

  • Figure 1: Overview of ACR tracking in smart TVs.
  • Figure 2: Experimental setup.
  • Figure 3: Methodology. The methodology is repeated for each scenario and TV in the two countries.
  • Figure 4: 10 minutes of ACR traffic in different scenarios during LIn-OIn in UK.
  • Figure 5: Cumulative distribution of bytes transmitted to ACR domains over the time during different opted-in phases in UK.
  • ...and 6 more figures