2 papers
cs.CR2023
Exact and Efficient Bayesian Inference for Privacy Risk Quantification (Extended Version)
Rasmus C. Rønneberg, Raúl Pardo, Andrzej Wąsowski
Data analysis has high value both for commercial and research purposes. However, disclosing analysis results may pose severe privacy risk to individuals. Privug is a method to quan…
cs.CR2022
Privacy with Good Taste: A Case Study in Quantifying Privacy Risks in Genetic Scores
Raúl Pardo, Willard Rafnsson, Gregor Steinhorn +5
Analysis of genetic data opens up many opportunities for medical and scientific advances. The use of phenotypic information and polygenic risk scores to analyze genetic data is wid…