Secure Sharing of Clinical History and Genetic Data


This project develops differential privacy versions of leading machine learning algorithms, and tests their preservation of utility when learning predictive models for personalized medicine. It also develops and tests secure local environments for ensuring end-to-end security, a secure virtual environment for privacy-preserving data analysis “in the cloud,” and anonymizing data publishing algorithms.


CS Collaborators: 

C David Page
Jeffrey Naughton
Somesh Jha

Campus Collaborators: 

Marchfield Clinic
Univ. of Texas


National Institutes of Health