Security for data analytics – gaining a grip on the two-edged sword

Prof. Dawn Song and graduate student Noah Johnson are taking a new approach to enable organizations to follow tight data security and privacy policies while enabling flexible data analysis, as well as machine learning for analysts.  Working with Uber, they tested their system using a dataset of 8 million queries written by the company’s data analysts. The system is currently being integrated into Uber’s internal data analytics platform.  With help from the Signatures Innovation Fellows program, they are advancing the system to provide the same level of security and flexibility for a broad range of data analysis and machine learning, whether needed in basic and medical research or business analytics.