Improving Utility for Privacy-Preserving Analysis of Correlated Columns using Pufferfish Privacy. (arXiv:2209.10908v1 [cs.CR])

Surveys are an important tool for many areas of social science research, but
privacy concerns can complicate the collection and analysis of survey data.
Differentially private analyses of survey data can address these concerns, but
at the cost of accuracy - especially for high-dimensional statistics. We
present a novel privacy mechanism, the Tabular DDP Mechanism, designed for
high-dimensional statistics with incomplete correlation. The Tabular DDP
Mechanism satisfies dependent differential privacy, a variant of Pufferfish
privacy; it works by building a …

analysis privacy utility