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In medical studies and mobile healthcare services, sharing of personal sensory information is inevitable. While we need to share such information, it is important to preserve privacy of individuals. The key challenge is balancing individual privacy and information utility. That is achieving a certain utility of the information while restricting or hiding sensitive information from personal data. We propose a privacy-preserving data sharing architecture to solve the problem. Our architecture provides several mechanisms: fine-grained access control, remote data stores, data obfuscation, and utility assessment. With our privacy mechanisms, individual can obtain control over who can access what information, choose where their data are physically stored, and restrict inferences that can be drawn using their data. In addition, using our utility assessment tool, medical study organizers can find study subjects who provide desired quality of information.
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