Mathematical Foundations of Data Privacy (18w5189)



(Princeton University)

Cynthia Dwork (Harvard University)

(University of Toronto)


The Banff International Research Station will host the "Mathematical Foundations of Data Privacy" workshop from April 29th to May 4th, 2018.

Widespread collection, analysis, and sharing of sensitive data has led to several high-profile privacy breaches. Often, these attacks involve linking an "anonymized'' dataset, having sensitive information, with a public dataset holding only neutral information. The failure of traditional methods for anonymizing data has demonstrated the need for a rigorous theory of private data analysis --- one which is robust against the use of both existing and unforseen outside sources of information. Over the past decade, differential privacy has emerged as the standard for privacy-preserving data analysis within the mathematical sciences.

This workshop will bring together researchers from different disciplines with a common interest in the mathematical foundations of data privacy. It will help the community understand the diverse challenges being tackled by current privacy research, share new algorithmic techniques for privacy-preserving data analysis, and discuss the most pressing directions for further research.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).