6 papers
Sequential Auditing for f-Differential Privacy
Tim Kutta, Martin Dunsche, Yu Wei +1
We present new auditors to assess Differential Privacy (DP) of an algorithm based on output samples. Such empirical auditors are common to check for algorithmic correctness and imp…
Differentially private testing for relevant dependencies in high dimensions
Patrick Bastian, Holger Dette, Martin Dunsche
We investigate the problem of detecting dependencies between the components of a high-dimensional vector. Our approach advances the existing literature in two important respects. F…
SILENT: A New Lens on Statistics in Software Timing Side Channels
Martin Dunsche, Patrick Bastian, Marcel Maehren +5
Cryptographic research takes software timing side channels seriously. Approaches to mitigate them include constant-time coding and techniques to enforce such practices. However, re…
General-Purpose -DP Estimation and Auditing in a Black-Box Setting
Önder Askin, Holger Dette, Martin Dunsche +4
In this paper we propose new methods to statistically assess -Differential Privacy (-DP), a recent refinement of differential privacy (DP) that remedies certain weaknesses of…
Lower Bounds for Rényi Differential Privacy in a Black-Box Setting
Tim Kutta, Önder Askin, Martin Dunsche
We present new methods for assessing the privacy guarantees of an algorithm with regard to Rényi Differential Privacy. To the best of our knowledge, this work is the first to addre…
Multivariate Mean Comparison under Differential Privacy
Martin Dunsche, Tim Kutta, Holger Dette
The comparison of multivariate population means is a central task of statistical inference. While statistical theory provides a variety of analysis tools, they usually do not prote…