Listen to the Voices of Everyday Users: Democratizing Privacy Ratings for Sensitive Data Access in Mobile Apps
Liu Wang, Tianshu Zhou, Haoyu Wang, Yi Wang

TL;DR
This paper introduces DePRa, a user-centric system for democratizing privacy ratings of mobile app data access, aiming to align privacy assessments with user perceptions and improve privacy regulation enforcement.
Contribution
It presents a novel participatory design approach and prototype system that actively involves users in privacy evaluation, complementing traditional expert audits.
Findings
DePRa effectively captures user opinions on sensitive data access.
User ratings show alignment with expert assessments.
Risk preference influences privacy score calibration.
Abstract
Mobile apps frequently request excessive data access, raising significant privacy concerns. While regulations like GDPR emphasize data minimization, they provide limited guidance on concretely defining and enforcing necessary data access. Existing regulatory mechanisms primarily rely on expert-driven audits that face challenges in scalability, neutrality, and alignment with user expectations. In this paper, we propose a novel paradigm--democratizing privacy assessment, inspired by prior work on user-centric privacy perceptions--which repositions users as active evaluators in the privacy auditing process, recognizing that user perceptions of data usage play a crucial role in assessing the appropriateness and necessity of data access. To operationalize this paradigm, we introduce DePRa, a prototype system developed through participatory design, featuring contextual explanation provision,…
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