Decentralized Differentially-Private Methods for Dynamic Data Release and Analysis (DECENTRALIZED)

 

PI:Xiaoqian Jiang
Co-PIs:Lucila Ohno-Machado
Trainees:Wenrui Dai
Grant:

R01GM118609

Start date of Project:

1/1/17 

Expected duration of Project:12/31/20
Description of Project:

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.

Additional links to other sites/Publications:https://projectreporter.nih.gov/project_info_description.cfm?aid=9239100&icde=33255844&ddparam=&ddvalue=&ddsub=&cr=1&csb=default&cs=ASC&pball=