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cs.CR2021
A unified interpretation of the Gaussian mechanism for differential privacy through the sensitivity index
Georgios Kaissis, Moritz Knolle, Friederike Jungmann +3
The Gaussian mechanism (GM) represents a universally employed tool for achieving differential privacy (DP), and a large body of work has been devoted to its analysis. We argue that…
cs.CR2021
Partial sensitivity analysis in differential privacy
Tamara T. Mueller, Alexander Ziller, Dmitrii Usynin +4
Differential privacy (DP) allows the quantification of privacy loss when the data of individuals is subjected to algorithmic processing such as machine learning, as well as the pro…