Using secure graph algorithms for the privacy-preserving identification of optimal bartering opportunities

Stefan Wüller, Michael Vu, Ulrike Meyer, Susanne Wetzel

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

10 Scopus citations

Abstract

We present a novel bartering protocol that allows multiple parties to identify their trade partners in a privacy-preserving fashion while maximizing the number of parties that can trade. Compared to existing approaches, the (polynomial) time complexity of our protocol is independent of the size of the search space which grows exponentially in the number of parties. At the core of our protocol is a novel privacy-preserving implementation of the Hungarian algorithm which allows multiple parties to compute a weighted maximum matching on a private input graph.

Original languageEnglish
Title of host publicationWPES 2017 - Proceedings of the 2017 Workshop on Privacy in the Electronic Society, co-located with CCS 2017
Pages123-132
Number of pages10
ISBN (Electronic)9781450351751
DOIs
StatePublished - 30 Oct 2017
Event16th ACM Workshop on Privacy in the Electronic Society, WPES 2017 - Dallas, United States
Duration: 30 Oct 2017 → …

Publication series

NameWPES 2017 - Proceedings of the 2017 Workshop on Privacy in the Electronic Society, co-located with CCS 2017
Volume2017-January

Conference

Conference16th ACM Workshop on Privacy in the Electronic Society, WPES 2017
Country/TerritoryUnited States
CityDallas
Period30/10/17 → …

Keywords

  • Bartering
  • E-Commerce
  • Homomorphic encryption
  • Privacy
  • Secure multi-party computation

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