Social networking and sensor-rich devices such as smartphones are becoming increasingly pervasive in today's society. People can share information concerning their location, activity, fitness, and health with their friends and family while benefiting from applications that leverage such information. Yet, users already find managing their privacy to be challenging, and the complexity involved in doing so is bound to increase. Usable techniques are required to enable people to effectively manage the dissemination of their private information as sensed by their mobile devices and sensors in their environment. This project explores `sensible' privacy controls and feedback mechanisms that allow people (or automated mechanisms acting on their behalf) to respond to unanticipated patterns and actual uses of their information in a way that is usable and intuitive. This approach has two advantages: 1) people need only care about the subset of data and usage scenarios that have the potential to violate their privacy, thus reducing the amount of data to which they must regulate access; and 2) people make better decisions concerning such access when these decisions are made in a context where they know how their data is being used. Sensible privacy mechanisms can have a profound and positive societal impact by not only helping people control their privacy, but also potentially increasing their participation in sensor-enabled computing because of this added control. This project firmly integrates education into the research through research experiences for underrepresented groups and the development of course modules on privacy at the undergraduate and graduate levels.
CAREER: Sensible Privacy: Pragmatic Privacy Controls in an Era of Sensor-Enabled Computing