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A Novel Analysis of Utility in Privacy Pipelines, Using Kronecker Products and Quantitative Information Flow
We combine Kronecker products, and quantitative information flow, to give a novel formal analysis for the fine-grained verification of utility in complex privacy pipelines. The combination explains a surprising anomaly in the behaviour of utility of privacy-preserving pipelines - that sometimes a reduction in privacy results also in a decrease in utility. We demonstrate our results on a number of common privacy-preserving designs.
Mário S. Alvim
,
Natasha Fernandes
,
Annabelle McIver
,
Carroll Morgan
,
Gabriel H. Nunes
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DOI
A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow
We combine Kronecker products, and quantitative information flow, to give a novel formal analysis for the fine-grained verification of utility in complex privacy pipelines. The combination explains a surprising anomaly in the behaviour of utility of privacy-preserving pipelines - that sometimes a reduction in privacy results also in a decrease in utility. We demonstrate our results on a number of common privacy-preserving designs.
Mário S. Alvim
,
Natasha Fernandes
,
Annabelle McIver
,
Carroll Morgan
,
Gabriel H. Nunes
Flexible and scalable privacy assessment for very large datasets, with an application to official governmental microdata
We present a systematic refactoring of the conventional treatment of privacy analyses, basing it on mathematical concepts from the framework of Quantitative Information Flow (QIF). We apply our approach to a very large case study: the Educational Censuses of Brazil, curated by the governmental agency INEP, which comprise over 90 attributes of approximately 50 million individuals released longitudinally every year since 2007.
Mário S. Alvim
,
Natasha Fernandes
,
Annabelle McIver
,
Carroll Morgan
,
Gabriel H. Nunes
PDF
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