Private Set Intersection and Compute

Flavio Bergamaschi (), Tancrède Lepoint (), Peter Leihn () and Sreekanth Kannepalli ()
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Flavio Bergamaschi: SRI International
Tancrède Lepoint: SRI International
Peter Leihn: SRI International
Sreekanth Kannepalli: Microsoft

A chapter in Protecting Privacy through Homomorphic Encryption, 2021, pp 97-104 from Springer

Abstract: Abstract We consider the scenario where two or more data owners would like to join their data and compute some functions over the intersection of their data in a privacy-preserving way and without disclosing their dataset to each other nor the intersection of their datasets. This scenario is primarily motivated by the following aspects:

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-77287-1_6

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DOI: 10.1007/978-3-030-77287-1_6

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