Privacy, Data Privacy, and Differential Privacy

This talk invites inquisitive audiences to explore the intricacies of data privacy, tracing its origins from the late 19th century to its critical importance in the digital age.

It examines Differential Privacy (DP) as a significant advancement in balancing data privacy with utility, highlighting the challenges and misconceptions that arise, particularly concerning the static view of individual data. Finally, it outlines the essential building blocks of DP and their application, using examples like the US Census, to illustrate both the theoretical and practical aspects of data privacy methodologies.

Organized by:

Department of Statistics LMU Munich