Privacy in the hands of the data analyzer - Seminar with Prof. Kobbi Nissim
Welcome to meet the prize winner, Prof. Kobbi Nissim, Computer Science at Georgetown University, that won the 2017 Gödel Prize for creating a new privacy concept now used by Google and Apple. He will present at our seminar "Privacy in the hands of the data analyzer". Welcome!
Abstract
Differential privacy is a robust concept of privacy. It brings mathematical rigor to the decades-old problem of privacy-preserving analysis of collections of sensitive personal information. Informally, differential privacy requires that the outcome of an analysis would remain stable under any possible change to an individual's information, and hence protects individuals from attackers that try to learn the information particular to them.
The rich research of differential privacy has uncovered deep connections to many research areas, including learning theory, cryptography, complexity theory, algorithmic game theory, and statistics. After a brief introduction to differential privacy, we will look into some of these connections, focusing on how differential privacy can serve as a tool for data analysis, even in cases where privacy is not a goal.
Short Bio
Prof. Kobbi Nissim is McDevitt Chair in Computer Science, Georgetown University. Nissim’s work is focused on the mathematical formulation and understanding of privacy. His work from 2003 and 2004 with Dinur and Dwork initiated rigorous foundational research of privacy and presented a precursor of Differential Privacy - a definition of privacy in computation that he introduced in 2006 with Dwork, McSherry and Smith. His research studies privacy in various contexts, including statistics, computational learning, mechanism design, social networks, and more recently law and policy. Since 2011, Nissim has been involved with the Privacy Tools for Sharing Research Data project at Harvard, developing privacy-preserving tools for the sharing of social-science data. Nissim was awarded the Godel Prize In 2017, the IACR TCC Test of Time Award in 2016, and the ACM PODS Alberto O. Mendelzon Test-of-Time Award in 2013.
