5 citations · 9 across the 12 of their papers we have counts for
13 papers
Tight Auditing of Differential Privacy in MST and AIM
Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Bogdan Kulynych
State-of-the-art Differentially Private (DP) synthetic data generators such as MST and AIM are widely used, yet tightly auditing their privacy guarantees remains challenging. We in…
CLIOPATRA: Extracting Private Information from LLM Insights
Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro, Peter Kairouz
The widespread adoption of AI assistants has prompted the development of privacy-aware platforms designed to extract insights from real-world usage. Their privacy protections prima…
A Unified Framework for Adversary-Aware Differential Privacy Bounds
Marika Swanberg, Meenatchi Sundaram Muthu Selva Annamalai, Jamie Hayes +2
Differential Privacy (DP) bounds the privacy leakage of a mechanism against worst-case membership inference, but the precise tradeoff between complex adversarial models and DP prot…
The Hitchhiker's Guide to Efficient, End-to-End, and Tight DP Auditing
Meenatchi Sundaram Muthu Selva Annamalai, Borja Balle, Jamie Hayes +2
In this paper, we systematize research on auditing Differential Privacy (DP) techniques, aiming to identify key insights and open challenges. First, we introduce a comprehensive fr…
Understanding the Impact of Data Domain Extraction on Synthetic Data Privacy
Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Sofiane Mahiou +1
Privacy attacks, particularly membership inference attacks (MIAs), are widely used to assess the privacy of generative models for tabular synthetic data, including those with Diffe…
The Importance of Being Discrete: Measuring the Impact of Discretization in End-to-End Differentially Private Synthetic Data
Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Sofiane Mahiou +1
Differentially Private (DP) generative marginal models are often used in the wild to release synthetic tabular datasets in lieu of sensitive data while providing formal privacy gua…