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20182022
most citedUniversal Optimality and Robust Utility Bounds for Metric Differential Privacy

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CR20222 cited

Universal Optimality and Robust Utility Bounds for Metric Differential Privacy

Natasha Fernandes, Annabelle McIver, Catuscia Palamidessi +1

We study the privacy-utility trade-off in the context of metric differential privacy. Ghosh et al. introduced the idea of universal optimality to characterise the best mechanism fo…

cs.CR2021

The Laplace Mechanism has optimal utility for differential privacy over continuous queries

Natasha Fernandes, Annabelle McIver, Carroll Morgan

Differential Privacy protects individuals' data when statistical queries are published from aggregated databases: applying "obfuscating" mechanisms to the query results makes the r…

cs.CR2019

Utility-Preserving Privacy Mechanisms for Counting Queries

Natasha Fernandes, Kacem Lefki, Catuscia Palamidessi

Differential privacy (DP) and local differential privacy (LPD) are frameworks to protect sensitive information in data collections. They are both based on obfuscation. In DP the no…

cs.CR2018

Generalised Differential Privacy for Text Document Processing

Natasha Fernandes, Mark Dras, Annabelle McIver

We address the problem of how to "obfuscate" texts by removing stylistic clues which can identify authorship, whilst preserving (as much as possible) the content of the text. In th…

cs.CR2018

Author Obfuscation Using Generalised Differential Privacy

Natasha Fernandes, Mark Dras, Annabelle McIver

The problem of obfuscating the authorship of a text document has received little attention in the literature to date. Current approaches are ad-hoc and rely on assumptions about an…