On Privacy and Accuracy in Data Releases (Invited Paper)
- M. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel H. Nunes
- Computer ScienceInternational Conference on Concurrency Theory
- 1 August 2020
A formal quantitative study of privacy in the publication of official educational censuses in Brazil
- Gabriel H. Nunes, M. Alvim, Annabelle McIver
- EconomicsAnais do XXXV Concurso de Teses e Dissertações…
- 31 July 2022
We present a summary of the work done in the dissertation "A formal quantitative study of privacy in the publication of official educational censuses in Brazil", including its contributions and…
On Privacy and Accuracy in Data Releases
- M. Alvim, Natasha Fernandes, Annabelle McIver, Gabriel H. Nunes
- Computer Science
- 2020
A model of quantitative information flow is used to describe the the trade-off between privacy of individuals’ data and and the utility of queries to that data by modelling the effectiveness of adversaries attempting to make inferences after a data release.
Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata
- M. Alvim, Natasha Fernandes, Annabelle McIver, Carroll Morgan, Gabriel H. Nunes
- Computer ScienceProceedings on Privacy Enhancing Technologies
- 28 April 2022
A systematic refactoring of the conventional treatment of privacy analyses is presented, basing it on mathematical concepts from the framework of Quantitative Information Flow (QIF), allowing for precise quantification and comparison of privacy risks for attacks both known and novel.