Efficient commodity matching for privacy-preserving two-party bartering

Fabian Förg, Susanne Wetzel, Ulrike Meyer

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

1 Scopus citations

Abstract

Current bartering platforms place the burden of finding si- multaneously executable quotes on their users. In addition, these bartering platforms do not keep quotes private. To address these shortcomings, this paper introduces a privacy-preserving bartering protocol secure in the semi-honest model. At its core, the novel bartering protocol uses a newly-developed bipartite matching protocol which determines simultaneously executable quotes in an efficient manner. While the new privacy-preserving bipartite matching protocol does not always yield the maximal set of simultaneously executable quotes, it keeps the parties' quotes private at all times. Moreover, our new privacy-preserving bipartite matching protocol is more efficient than existing solutions in that it only requires linear communication in the number of quotes the parties specify.

Original languageEnglish
Title of host publicationCODASPY 2017 - Proceedings of the 7th ACM Conference on Data and Application Security and Privacy
Pages107-114
Number of pages8
ISBN (Electronic)9781450345231
DOIs
StatePublished - 22 Mar 2017
Event7th ACM Conference on Data and Application Security and Privacy, CODASPY 2017 - Scottsdale, United States
Duration: 22 Mar 201724 Mar 2017

Publication series

NameCODASPY 2017 - Proceedings of the 7th ACM Conference on Data and Application Security and Privacy

Conference

Conference7th ACM Conference on Data and Application Security and Privacy, CODASPY 2017
Country/TerritoryUnited States
CityScottsdale
Period22/03/1724/03/17

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