Position Paper: Towards Ubiquitous and Automated User Privacy Configuration


Song Liao, Jingwen Yan, Yichen Liu, David Kotz, Luyi Xing, and Long Cheng. Position Paper: Towards Ubiquitous and Automated User Privacy Configuration. Proceedings of the Workshop on Security and Privacy in Standardized IoT (SDIoTSec'26). Internet Society, February 2026. doi:10.14722/sdiotsec.2026.23043. ©Copyright Internet Society.

Abstract:

Mobile apps may collect, share, and analyze data from users. Although users can choose to decline apps' data collection behaviors through mobile permission systems or in-app settings, it is challenging and time-consuming for users to manually discover and correctly configure all the privacy settings for apps on their mobile phones. This issue also occurs in IoT apps, where users need to configure each device separately. Although they can manage some settings with platform apps (like Apple Home), many IoT devices expose device-specific settings within a device-specific app. In this position paper, we propose the PrivacyProfile, a framework that allows users to easily set their global privacy preferences and apply them to apps automatically. Users can indicate whether each of their privacy-related information can be collected, shared, and analyzed in their profile. Compatible apps then read the privacy profile and automatically configure their settings for users, e.g., enabling data collection behaviors or disabling data sharing. This design enables users to easily configure their privacy preferences once, rather than having to manually open each app and locate the corresponding privacy settings.

Citable with [BibTeX]: \cite{liao:position}

Projects: [splice]

Keywords: [iot] [software]

Available from the publisher: [DOI]

Available from the author: [bib] [pdf]
This pdf was produced by the publisher and its posting here is permitted by the publisher.

thumbnail image

[Kotz research]