A large and increasing number of services rely on data and measurements collected from mobile devices and shared with a centralized entity. Users enjoy these services (such as location-based services, recommendations, wireless connectivity and others) at the expense of sharing data from their mobile devices, which increases their privacy risk. For example, users may want to receive a location-based service, but they may be concerned about sending their exact location to a server or third parties. Recently, there has been increased awareness and concern about preserving user privacy, while still empowering the services that big data enable. While privacy has become a significant societal concern, the technical solutions in this domain are still lagging behind, and there is a gap between the theory of privacy and practices in the mobile ecosystem. This project will develop principled techniques for controlling the privacy-utility tradeoff for mobile data. Broader impact activities include collaborations with major players in the space of wireless networking and mobile data crowdsourcing, training students and broadening participation in computing.
In this project, we focus specifically on data reported from mobile devices, including information about the wireless network, as well as personal/user data. Our goal is to develop privacy-preserving techniques to obfuscate reported data, while still providing guarantees for the quality of the provided service. We will develop both the theoretical framework (privacy-utility formulation, optimization of obfuscation techniques, and heuristic algorithms), as well as its application to wireless spectrum sharing, cellular signal maps, and personal information tracking. The project will produce models, algorithms, datasets, mobile system implementations and programming interfaces, which trade off utility vs. privacy in a principled and transparent way.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
