77 citations · 340 across the 32 of their papers we have counts for
37 papers
Forward and Backward Simulations for Partially Observable Probability
Chris Chen, Annabelle McIver, Carroll Morgan
Data refinement is the standard extension of a refinement relation from programs to datatypes (i.e. a behavioural subtyping relation). Forward/backward simulations provide a tracta…
The Privacy-Utility Trade-off in the Topics API
Mário S. Alvim, Natasha Fernandes, Annabelle McIver +1
The ongoing deprecation of third-party cookies by web browser vendors has sparked the proposal of alternative methods to support more privacy-preserving personalized advertising on…
Bayes' capacity as a measure for reconstruction attacks in federated learning
Sayan Biswas, Mark Dras, Pedro Faustini +4
Within the machine learning community, reconstruction attacks are a principal attack of concern and have been identified even in federated learning, which was designed with privacy…
Source-level reasoning for quantitative information flow
Chris Chen, Annabelle McIver, Carroll Morgan
We present a novel formal system for proving quantitative-leakage properties of programs. Based on a theory of Quantitative Information Flow (QIF) that models information leakage a…
A Quantitative Information Flow Analysis of the Topics API
Mário S. Alvim, Natasha Fernandes, Annabelle McIver +1
Third-party cookies have been a privacy concern since cookies were first developed in the mid 1990s, but more strict cookie policies were only introduced by Internet browser vendor…
A novel analysis of utility in privacy pipelines, using Kronecker products and quantitative information flow
Mário S. Alvim, Natasha Fernandes, Annabelle McIver +2
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 com…