Lead PI Salil Vadhan will present "Differential Privacy: Theoretical and Practical Challenges," at NSF on Thursday, January 15th. This presentation is part of NSF’s Washington Area Trustworthy Computing Hour (WATCH) seminar series.
Abstract:
Differential Privacy is framework for enabling the analysis of privacy-sensitive datasets while ensuring that individual-specific information is not revealed. The concept was developed in a body of work in theoretical computer science starting about a decade ago. It is now flourishing as an area of research, with deep connections to many other topics in theory. At the same time, its potential for addressing pressing privacy problems in a variety of domains has attracted the interest of scholars from many other areas, including statistics, databases, medical informatics, law, social science, computer security and programming languages.
In this talk, I will give a general introduction to differential privacy, and discuss some of the theoretical and practical challenges for future work in this area. I will also describe a large, multidisciplinary research project at Harvard, called "Privacy Tools for Sharing Research Data," in which we are working on some of these challenges as well as others associated with the collection, analysis, and sharing of personal data for research in social science and other fields.