Crowdsourcing for Context: Regarding Privacy in Beacon Encounters via Contextual Integrity

Abstract

Abstract Research shows that context is important to the privacy perceptions associated with technology. With Bluetooth Low Energy beacons, one of the latest technologies for providing proximity and indoor tracking, the current identifiers that characterize a beacon are not sufficient for ordinary users to make informed privacy decisions about the location information that could be shared. One solution would be to have standardized category and privacy labels, produced by beacon providers or an independent third-party. An alternative solution is to find an approach driven by users, for users. In this paper, we propose a novel crowdsourcing based approach to introduce elements of context in beacon encounters.We demonstrate the effectiveness of this approach through a user study, where participants use a crowd-based mobile app designed to collect beacon category and privacy information as a scavenger hunt game. Results show that our approach was effective in helping users label beacons according to the specific context of a given beacon encounter, as well as the privacy perceptions associated with it. This labeling was done with an accuracy of 92%, and with an acceptance rate of 82% of all recommended crowd labels. Lastly, we conclusively show how crowdsourcing for context can be used towards a user-centric framework for privacy management during beacon encounters.