New Privacy Frameworks for Collaborative Information Sharing

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The goal of this project is to develop new concepts and frameworks for privacy in collaborative environments, focusing on global properties of the joint dataset such as security against unreasonable searches and abusive information harvesting. Techniques include provably secure data transformations that assure global and individual privacy properties after information has been released in response to a legitimate request. To enforce global privacy policies, this project will develop new cryptographic techniques for dataset obfuscation and sanitization, ensuring that only policy-compliant queries can be computed on the dataset after it has been transferred to the collaborators. The main objective is to design privacy-preserving data transformations that are provably secure without unrealistic assumptions about "tamper-proof" software or hardware.

This project is supported by the NSF grants IIS-0534198 and IIS-0534052 (Jan 1, 2006 - Dec 31, 2009).



Contact: shmat AT cs DOT utexas DOT edu