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To address privacy concerns with the Internet of Things (IoT) devices, researchers have proposed enhancements in data collection transparency and user control. However, managing privacy preferences for shared devices with multiple stakeholders remains challenging. We introduced ThingPoll, a system that helps users negotiate privacy configurations for IoT devices in shared settings. We designed ThingPoll by observing twelve participants verbally negotiating privacy preferences, from which we identified potentially successful and inefficient negotiation patterns. ThingPoll bootstraps a preference model from a custom crowdsourced privacy preferences dataset. During negotiations, ThingPoll strategically scaffolds the process by eliciting users’ privacy preferences, providing helpful contexts, and suggesting feasible configuration options. We evaluated ThingPoll with 30 participants negotiating the privacy settings of 4 devices. Using ThingPoll, participants reached an agreement in 97.5% of scenarios within an average of 3.27 minutes. Participants reported high overall satisfaction of 83.3% with ThingPoll as compared to baseline approaches.
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This content will become publicly available on July 20, 2027
VBIT: Towards Enhancing Privacy Control Over IoT Devices
Internet of Things (IoT) devices are increasingly deployed at home, at work, and in other shared and public spaces. IoT devices collect and share data with service providers and third parties, which poses privacy concerns. Although privacy-enhancing tools are quite advanced in other application domains (e.g., advertising and tracker blockers for browsers), users currently have no convenient way to know or manage the data that is collected and shared by IoT devices. In order to understand what users expect from such tools, we present and evaluateVBIT, an interactive system combining Mixed Reality (MR) and web-based applications that allows users to: (1) uncover and visualize tracking services by IoT devices in an instrumented space and (2) take action to stop or limit that tracking. We design and implementVBITto operate at the network traffic level, and we show that it has negligible performance overhead and offers both flexibility and good usability. We perform a mixed-method user study consisting of an online survey and an in-person interview study. We show that users appreciate transparency, control, and customization features, and they become significantly more willing to install an IoT advertising and tracking blocker, as demonstrated by their experience usingVBIT. We also obtain design insights that can be used to further iterate and improve the design ofVBITand other systems for IoT transparency and control.
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- Award ID(s):
- 1956393
- PAR ID:
- 10708132
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM Transactions on Internet of Things
- ISSN:
- 2691-1914
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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