3 papers
cs.CR2026
The Adverse Effects of Omitting Records in Differential Privacy: How Sampling and Suppression Degrade the Privacy--Utility Tradeoff (Long Version)
Ãlex Miranda-Pascual, Javier Parra-Arnau, Thorsten Strufe
Sampling is renowned for its privacy amplification in differential privacy (DP), and is often assumed to improve the utility of a DP mechanism by allowing a noise reduction. In thi…
cs.CR2025
Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy
Martin Lange, Patricia Guerra-Balboa, Javier Parra-Arnau +1
Privacy risks in differentially private (DP) systems increase significantly when data is correlated, as standard DP metrics often underestimate the resulting privacy leakage, leavi…
cs.CR2024
Composition in Differential Privacy for General Granularity Notions (Long Version)
Patricia Guerra-Balboa, Ãlex Miranda-Pascual, Javier Parra-Arnau +1
The composition theorems of differential privacy (DP) allow data curators to combine different algorithms to obtain a new algorithm that continues to satisfy DP. However, new granu…