Cloud computing is gain popularity due to its cost-effective storage and computation. There are few studies on how to leverage cloud computing resources to facilitate healthcare research in a privacy preserving manner. This project proposes an advanced framework that combines rigorous privacy protection and encryption techniques to facilitate healthcare data sharing in the cloud environment. Comparing to traditional centralized data anonymization, we are facing major challenges such as lack of global knowledge and the difficulty to enforce consistency. We adopt differential privacy as our privacy criteria and will leverage homomorphic encryption and Yao's garbled circuit protocol to build secure yet scalable information exchange to overcome the barrier.
Sustainability and privacy are critical concerns in handling large and growing healthcare data. New challenges emerge as new paradigms like cloud computing become popular for cost-effective storage and computation. This project will develop an advanced framework to combine rigorous privacy protection and encryption techniques to facilitate healthcare data sharing in the cloud environment.
|Zhao, Yongan; Wang, Xiaofeng; Jiang, Xiaoqian et al. (2015) Choosing blindly but wisely: differentially private solicitation of DNA datasets for disease marker discovery. J Am Med Inform Assoc 22:100-8|