Measuring Risks to Users' Health Privacy Posed by Third-Party Web Tracking and Targeted Advertising

要旨

Online advertising platforms may be able to infer privacy-sensitive information about people, such as their health conditions. This could lead to harms like exposure to predatory targeted advertising or unwanted disclosure of health conditions to employers or insurers. In this work, we experimentally evaluate whether online advertisers target people with health conditions. We collected the browsing histories of people with and without health conditions. We crawled their histories to simulate their browsing profiles and collected the ads that were served to them. Then, we compared the content of the ads between groups. We observed that the profiles of people who visited more health-related web pages received more health-related ads. 49.5% of health-related ads used deceptive advertising techniques. Our findings suggest that new privacy regulations and enforcement measures are needed to protect people's health privacy from online tracking and advertising platforms.

著者
Eric W. Zeng
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Xiaoyuan Wu
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Emily N. Ertmann
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Lily Huang
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Danielle F. Johnson
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Anusha T. Mehendale
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Brandon T. Tang
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Karolina Zhukoff
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Michael Adjei-Poku
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Lujo Bauer
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Ari Friedman
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Matthew McCoy
University of Pennsylvania, Philadelphia, Pennsylvania, United States
DOI

10.1145/3706598.3714318

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714318

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Engaging Users for Security and Privacy

G418+G419
7 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
日本語まとめ
読み込み中…