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S&P2026顶会

Usable Anonymity in Reproductive Health Privacy

Qiurong Song, Yanlai Wu, Rie Helene Hernandez, Yao Li, Yubo Kou, Xinning Gui

2026年份
1被引次数

摘要

Anonymity is a key strategy for internet users to manage privacy and mitigate data surveillance risks. While tools like Tor support strong anonymity, they are often inaccessible to non-technical users, who instead rely more on platforms' built-in privacy features to seek anonymity. However, the usability of these features remains underexplored. This study focuses on period and fertility tracking (PFT) apps as a research context due to heightened privacy concerns about reproductive health surveillance, which intensify users’ need for usable privacy designs to achieve anonymity. We conducted usability testing with 32 participants across six PFT apps, revealing that the usability of anonymity-preserving features (APFs) significantly influences users' privacy perceptions. We identified key usability challenges, such as a lack of transparency regarding APFs and unintuitive processes for avoiding disclosure of personally identifiable information (PII). To address these issues, we propose recommendations for more accessible and usable anonymity in online platforms.

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