Turtle Guard: Helping Android Users Apply Contextual Privacy Preferences

Lynn Tsai, Primal Wijesekera, Joel Reardon, Irwin Reyes, Serge Egelman, David A. Wagner, Nathan Good, Jung-Wei Chen
2017 Symposium On Usable Privacy and Security  
Current mobile platforms provide privacy management interfaces to regulate how applications access sensitive data. Prior research has shown how these interfaces are insufficient from a usability standpoint: they do not account for context. In allowing for more contextual decisions, machine-learning techniques have shown great promise for designing systems that automatically make privacy decisions on behalf of the user. However, if such decisions are made automatically, then feedback mechanisms
more » ... re needed to empower users to both audit those decisions and correct any errors. In this paper, we describe our user-centered approach towards designing a fully functional privacy feedback interface for the Android platform. We performed two large-scale user studies to research the usability of our design. Our second, 580-person validation study showed that users of our new interface were significantly more likely to both understand and control the selected set of circumstances under which applications could access sensitive data when compared to the default Android privacy settings interface. The popular open-source Android mobile platform has used two general approaches to give users control over permissions. Initially, permissions were presented as an install-
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