Understanding Trade-offs Between Worst-case Differential Privacy Guarantees & Real Threat Models
Explores the nuanced trade-offs between theoretical worst-case differential privacy guarantees and practical real-world threat models. Examines challenges in interpreting and applying DP in diverse contexts.
A Google TechTalk, 2026-05-20, presented by Meenatchi Sundaram Muthu Selva Annamalai
Full Title: Theory will only take you so far: Understanding the precise trade-offs between worst-case differential privacy guarantees and real-world threat models
ABSTRACT: Although DP is a popular framework that has transformed the space of privacy-preserving data analysis in the past 23 years, a central challenge that remains is how to interpret and translate the worst-case privacy protections to real world threat models. In this talk, I will present several work that attempt to tackle this challenge from both theoretical and empirical angles. On the theory side, careful edge-case analysis and incorporation of priors has enabled us to more accurately upper-bound real-world adversaries’ performance against DP mechanisms. On the other hand, better auditing mechanisms have paved the way for more accurate lower-bounds empirically. Nevertheless, a substantial gap still exists between the two bounds, for which I identify and present several promising directions for future research.