A PLATFORM FOR CONTEXTUAL MOBILE PRIVACY
Technical Report,01 Jun 2016,31 Jul 2017
INTERNATIONAL COMPUTER SCIENCE INST BERKELEY CA BERKELEY United States
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We developed a system that balances the privacy needs of users and organizations when using personal devices in the workplace-- Bring Your Own Device BYOD environments. In so doing, we performed qualitative interviews with extreme users, to under- stand their privacy needs, the shortcomings of current systems, and their existing coping mechanisms. Based on these interviews, we developed a system that applies machine-learning to automatically infer when access to sensitive data is likely to be expected by the user. We performed a field study to collect real-world training data to train the classifier offline. In parallel, we performed an online study to evaluate designs for a user interface i.e., a privacy management dashboard. Based on our study results, we implemented our designs into the Android platform and performed a subsequent field study to validate our designs.
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