Events Calendar

CS Colloquium

Speaker: Guy Rothblum, Princeton University

Talk Title: Differential Privacy: Recent Developements and Future Challenges

Abstract: Consider a database of sensitive information about a set of participants. Statistical analysis of the data may yield valuable results, but it also poses serious threats to the participants' privacy. A successful research program has, in the last few years, attempted to address these conflicting concerns, formulating the rigorous privacy guarantee of differential privacy [Dwork McSherry Nissim and Smith '06] and showing that in some cases data analyses can provide accurate answers while protecting participants' privacy.

After reviewing some of this past work, I will introduce two new general-purpose tools for privacy-preserving data analysis:
1. A new "boosting" framework for improving the accuracy guarantees of weak differentially private algorithms.
2. Robust privacy guarantees for differentially private algorithms under composition.

Using these tools we will show that, computational complexity aside, differential privacy permits surprisingly rich and accurate data analyses. I will then highlight some of the intriguing challenges that remain open for future work in this field. No prior knowledge will be assumed.

Biography: Guy Rothblum is a postdoctoral research fellow at Princeton University, supported by a Computing Innovation Fellowship. He completed his Ph.D. in computer science at MIT, and his M.Sc. in computer Science and Applied Mathematics at the Weizmann Institute of Science. His research interests are in theoretical computer science and computer security, especially privacy-preserving data analysis, cryptography and complexity theory.

Host: Prof. Ming-Deh Huang

Location: Seaver Science Library (SSL) - 150

Audiences: Everyone Is Invited

Contact: Kanak Agrawal