Listen to the Voices of Everyday Users: Democratizing Privacy Ratings for Sensitive Data Access in Mobile Apps
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866910168594251776 |
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| author | Wang, Liu Zhou, Tianshu Wang, Haoyu Wang, Yi |
| author_facet | Wang, Liu Zhou, Tianshu Wang, Haoyu Wang, Yi |
| contents | 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, category-based representative selection, an intuitive rating interface, and preference-based rating adjustment. We evaluated DePRa with 200 everyday mobile app users, analyzing how effectively it captures user opinions on sensitive data access, comparing their privacy ratings with expert assessments, and exploring risk preference-based score calibration. Our findings show the feasibility and promise of democratized privacy assessment, highlighting its potential to complement expert auditing and support inclusive privacy evaluation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_24066 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Listen to the Voices of Everyday Users: Democratizing Privacy Ratings for Sensitive Data Access in Mobile Apps Wang, Liu Zhou, Tianshu Wang, Haoyu Wang, Yi Cryptography and Security Human-Computer Interaction 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, category-based representative selection, an intuitive rating interface, and preference-based rating adjustment. We evaluated DePRa with 200 everyday mobile app users, analyzing how effectively it captures user opinions on sensitive data access, comparing their privacy ratings with expert assessments, and exploring risk preference-based score calibration. Our findings show the feasibility and promise of democratized privacy assessment, highlighting its potential to complement expert auditing and support inclusive privacy evaluation. |
| title | Listen to the Voices of Everyday Users: Democratizing Privacy Ratings for Sensitive Data Access in Mobile Apps |
| topic | Cryptography and Security Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.24066 |