33 citations · 97 across the 23 of their papers we have counts for
7 papers · 1 filter
Not fit for Purpose: A critical analysis of the 'Five Safes'
Chris Culnane, Benjamin I. P. Rubinstein, David Watts
Adopted by government agencies in Australia, New Zealand and the UK as policy instrument or as embodied into legislation, the 'Five Safes' framework aims to manage risks of releasi…
Assessing Centrality Without Knowing Connections
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
We consider the privacy-preserving computation of node influence in distributed social networks, as measured by egocentric betweenness centrality (EBC). Motivated by modern communi…
Differentially-Private Two-Party Egocentric Betweenness Centrality
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
We describe a novel protocol for computing the egocentric betweenness centrality of a node when relevant edge information is spread between two mutually distrusting parties such as…
Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham +6
Despite the successful application of machine learning (ML) in a wide range of domains, adaptability---the very property that makes machine learning desirable---can be exploited by…
Options for encoding names for data linking at the Australian Bureau of Statistics
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
Publicly, ABS has said it would use a cryptographic hash function to convert names collected in the 2016 Census of Population and Housing into an unrecognisable value in a way that…
Vulnerabilities in the use of similarity tables in combination with pseudonymisation to preserve data privacy in the UK Office for National Statistics' Privacy-Preserving Record Linkage
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
In the course of a survey of privacy-preserving record linkage, we reviewed the approach taken by the UK Office for National Statistics (ONS) as described in their series of report…