Security on Two-Party Differentially Private Data

In this project study the problem of answering queries about private data that is spread across multiple different databases. For instance, a medical researcher may want to study a possible correlation between travel patterns and certain types of illnesses. The necessary information exists today suppose in airline reservation systems and hospital records but it is maintained by two separate companies who are prevented by law from sharing this information with each other, or with a third party. This separation prevents the processing of such queries, even if the final answer, e.g., a correlation coefficient, would be safe to release. Here present DJoin, a system that can process such distributed queries and can give strong differential privacy guarantees on the result. DJoin can support many SQL queries, including joins of databases maintained by different entities. This experimental evaluation shows that DJoin can process realistic queries at practical timescales. This project can be viewed as a special case of a more general approach for producing synthetic data.