On Privacy and Accuracy in Data Releases (Invited Paper)

DOI10.4230/LIPIcs.CONCUR.2020.1OpenAlexW3082340300MaRDI QIDQ5089262

Gabriel H. Nunes, Mário S. Alvim, Natasha Fernandes, Annabelle McIver

Publication date: 18 July 2022

Full work available at URL: https://drops.dagstuhl.de/opus/volltexte/2020/12813/pdf/LIPIcs-CONCUR-2020-1.pdf/

zbMATH Keywords

quantitative information flowinference attacksprivacy/utility trade-off

Mathematics Subject Classification ID

Models and methods for concurrent and distributed computing (process algebras, bisimulation, transition nets, etc.) (68Q85)

Cites Work

• Unnamed Item
• A Mathematical Theory of Communication
• The science of quantitative information flow
• Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias
• Pufferfish
• On the Foundations of Quantitative Information Flow
• Theory of Cryptography

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