12 - 16 February 2017, 7th BIU Winter School on Cryptography, Ramat-Gan, Israel

The concept of differential privacy is central to the rigorous foundational approach to private data analysis that has emerged in cryptography in the last decade. The development of this approach was motivated by the vast amounts of personal information that are collected in today’s information environment, and by a rapidly growing body of work demonstrating how traditional approaches to privacy, such as de-identification, fail to provide adequate privacy preservation.

The framework of differential privacy provides a rigorous mathematical treatment of privacy, with concrete provable guarantees that are robust against adversaries with arbitrary computational power and with arbitrary auxiliary knowledge. There is now a large body of theoretical work in this vein, and many established relationships to scientific fields including statistics, machine learning, databases, algorithms, information theory, program verification, and game theory. The products of this research are also making their first strides into use in real world applications where sensitive personal information is analyzed, with algorithms currently deployed by the US Census Bureau, Google, Yahoo, and Apple.

The target audience for the school is graduate students and postdocs in cryptography (we will assume that participants have taken at least one university-level course in cryptography). However, all faculty, undergrads and professionals with the necessary background are welcome. The winter school is open to participants from all over the world; all talks will be in English.