Fast and Private Computation of Cardinality of Set Intersection and Union

By Emiliano De Cristofaro, Paolo Gasti, Gene Tsudik. 2012

249 citations recorded by the source corpus.

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In Artificial Intelligence

Citations in the corpus

Secure Federated Submodel Learning (2019, background): “Compared with Private Set Intersection (PSI) [72]–[77] and Private Set union Cardinality (PSC) [78]– [80], which have received tremendous attention and also have seen several practical applications, such as in social networks [81], [82]; human genome testing [83]; location-based services [84]; secur”
Labeled PSI from Fully Homomorphic Encryption with Malicious Security (2018, background): “A recent trend in PSI protocols has been to enable additional computation on the intersection [19, 20, 30, 44].”
An Efficient Toolkit for Computing Private Set Operations (2017, methodology): “Dedicated techniques for computing these operations are given in [5,11,9] though designs are also given in the generic constructions of [18,1].”
Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs (2020, background): “[27; 28; 29] and private set intersection (cardinality) [30; 31; 32; 33] protocols seem especially relevant.”
On Deploying Secure Computing Commercially: Private Intersection-Sum Protocols and their Business Applications (2019, background): “Several works limit the parties to learning only the cardinality of the intersection [25, 1, 33, 51, 14, 40, 30].”
Distributed Measurement with Private Set-Union Cardinality (2017, background): “Several protocols to securely compute set-union cardinality (or the related problem of set-intersection cardinality) have been proposed [12, 18, 32, 48].”