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User Controllable Security & Privacy for Mobile Social Networking

Researchers: Norman Sadeh, Lorrie Cranor, Jason Hong

Research Area: Mobility | Privacy Protection

Cross Cutting Thrusts: Usable Privacy and Security

Abstract

Scope:  Leverage Locaccino to develop and evaluate several new technologies and to gain a deeper understanding of people's location sharing privacy policies; including running the first live pilot of a new family of user-controllable policy learning techniques capable of helping users refine policies through suggestions of incremental, human-understandable policy modifications; as well as extending a new theory of efficiency in the design of expressive mechanisms to the selection of expressive attributes in security and privacy policy, taking into account both accuracy and user burden considerations.

Outcomes: User-controllable learning technology; theory of efficiency in the design of expressive mechanisms applied to design of rich, yet usable security and privacy policy languages; new data mining methodology to identify understandable default policies that effectively reduce user burden in the specification of rich security and privacy policies; and better understanding of people's location sharing preferences.

Technical Reports: A Diary Study of Password Usage in Daily Life | When Are Users Comfortable Sharing Locations with Advertisers?