Secure Statistical Analysis on Multiple Datasets: Join and Group-By

Gilad Asharov, Koki Hamada, Ryo Kikuchi, Ariel Nof, Benny Pinkas, Junichi Tomida

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We implement a secure platform for statistical analysis over multiple organizations and multiple datasets. We provide a suite of protocols for different variants of JOIN and GROUP-BY operations. JOIN allows combining data from multiple datasets based on a common column. GROUP-BY allows aggregating rows that have the same values in a column or a set of columns, and then apply some aggregation summary on the rows (such as sum, count, median, etc.). Both operations are fundamental tools for relational databases. One example use case of our platform is in data marketing in which an analyst would join purchase histories and membership information, and then obtain statistics, such as "Which products were bought by people earning this much per annum?" Both JOIN and GROUP-BY involve many variants, and we design protocols for several common procedures. In particular, we propose a novel group-by-median protocol that has not been known so far. Our protocols rely on sorting protocols, and work in the honest majority setting and against malicious adversaries. To the best of our knowledge, this is the first implementation of JOIN and GROUP-BY protocols secure against a malicious adversary.

Original languageEnglish
Title of host publicationCCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery, Inc
Pages3298-3312
Number of pages15
ISBN (Electronic)9798400700507
DOIs
StatePublished - 15 Nov 2023
Event30th ACM SIGSAC Conference on Computer and Communications Security, CCS 2023 - Copenhagen, Denmark
Duration: 26 Nov 202330 Nov 2023

Publication series

NameCCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

Conference

Conference30th ACM SIGSAC Conference on Computer and Communications Security, CCS 2023
Country/TerritoryDenmark
CityCopenhagen
Period26/11/2330/11/23

Bibliographical note

Publisher Copyright:
© 2023 Copyright held by the owner/author(s).

Keywords

  • Privacy-preserving protocols
  • group-by
  • honest majority
  • join
  • multiparty computation

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