A privacy-preserving algorithm for distributed constraint optimization

Tal Grinshpoun, Tamir Tassa

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

Abstract

Distributed constraint optimization problems enable the representation of many combinatorial problems that are distributed by nature. An important motivation for such problems is to preserve the privacy of the participating agents during the solving process. The present paper introduces a novel privacy-preserving algorithm for this purpose. The proposed algorithm requires a secure solution of several multiparty computation problems. Consequently, appropriate novel secure protocols are devised and analyzed.

Original languageEnglish
Title of host publication13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages909-916
Number of pages8
ISBN (Electronic)9781634391313
StatePublished - 2014
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: 5 May 20149 May 2014

Publication series

Name13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Volume2

Conference

Conference13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Country/TerritoryFrance
CityParis
Period5/05/149/05/14

Bibliographical note

Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Keywords

  • Constraint privacy
  • DCOP
  • Search

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