Crowdsourced exploration of security configurations

Abstract

Smartphone apps today request permission to access a multitude of sensitive resources, which users must accept completely during installation (e.g., on Android) or selectively configure after installation (e.g., on iOS, but also planned for Android). Everyday users, however, do not have the ability to make informed decisions about which permissions are essential for their usage. For enhanced privacy, we seek to leverage crowdsourcing to find minimal sets of permissions that will preserve the usability of the app for diverse users. We advocate an efficient 'lattice-based' crowd-management strategy to explore the space of permissions sets. We conducted a user study (N = 26) in which participants explored different permission sets for the popular Instagram app. This study validates our efficient crowd management strategy and shows that usability scores for diverse users can be predicted accurately, enabling suitable recommendations.