Eran Toch, Justin Cranshaw, Paul Hankes-Drielsma, Jay Springfield, Patrick Gage Kelley, L. Cranor, Jason Hong, Norman Sadeh
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Locaccino is a location sharing application designed to empower users to effectively control their privacy. It has been piloted by close to 2000 users and has been used by researchers as an experimental platform for conducting research on location-based social networks. Featured technologies include expressive privacy rule creation, detailed feedback mechanisms that help users understand their privacy, algorithms for analyzing privacy preferences, and clients for mobile computers and smartphone devices. In addition, variations of Locaccino are also being piloted as part of research on user-controllable policy learning, learning usable privacy personas and reconciling expressiveness and user burden. The purpose of this demo is to introduce participants to the features of Locaccino, so that they can try out the Locaccino smartphone and laptop applications on their own devices, locate their friends and colleagues, and set rich privacy policies for sharing their location.
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