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Leveraging the "Multi" in secure multi-party computation

Published: 30 October 2003 Publication History

Abstract

Secure Multi-Party Computation enables parties with private data to collaboratively compute a global function of their private data, without revealing that data. The increase in sensitive data on networked computers, along with improved ability to integrate and utilize that data, make the time ripe for practical secure multi-party computation. This paper surveys approaches to secure multi-party computation, and gives a method whereby an efficient protocol for two parties using an untrusted third party can be used to construct an efficient peer-to-peer secure multi-party protocol.

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cover image ACM Conferences
WPES '03: Proceedings of the 2003 ACM workshop on Privacy in the electronic society
October 2003
135 pages
ISBN:1581137761
DOI:10.1145/1005140
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 October 2003

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Author Tags

  1. privacy
  2. secure distributed computation
  3. secure multi-party computation

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  • (2024)Secure IoT Communication: Implementing a One-Time Pad Protocol with True Random Numbers and Secure Multiparty SumsApplied Sciences10.3390/app1412535414:12(5354)Online publication date: 20-Jun-2024
  • (2017)Secure and scalable deduplication of horizontally partitioned health data for privacy-preserving distributed statistical computationBMC Medical Informatics and Decision Making10.1186/s12911-016-0389-x17:1Online publication date: 3-Jan-2017
  • (2015)A distributed decision support algorithm that preserves personal privacyJournal of Intelligent Information Systems10.1007/s10844-014-0331-644:1(107-132)Online publication date: 1-Feb-2015
  • (2013)Towards privacy-preserving computing on distributed electronic health record dataProceedings of the 2013 Middleware Doctoral Symposium10.1145/2541534.2541593(1-6)Online publication date: 9-Dec-2013
  • (2013)Distributing trusted third partiesACM SIGACT News10.1145/2491533.249155344:2(92-112)Online publication date: 3-Jun-2013
  • (2012)Privacy Preserving Integration of Health Care DataInnovations in Data Methodologies and Computational Algorithms for Medical Applications10.4018/978-1-4666-0282-3.ch007(94-107)Online publication date: 2012
  • (2012)Practical Multi-party Versions of Private Set Intersection Protocols with Hardware TokensComputer Applications for Communication, Networking, and Digital Contents10.1007/978-3-642-35594-3_10(72-79)Online publication date: 2012
  • (2012)Assisting server for secure multi-party computationProceedings of the 6th IFIP WG 11.2 international conference on Information Security Theory and Practice: security, privacy and trust in computing systems and ambient intelligent ecosystems10.1007/978-3-642-30955-7_13(144-159)Online publication date: 20-Jun-2012
  • (2012)Single and Multi Trusted Third Party: Comparison, Identification and Reduction of Malicious Conduct by Trusted Third Party in Secure Multiparty Computing ProtocolAdvances in Computer Science, Engineering & Applications10.1007/978-3-642-30111-7_28(295-304)Online publication date: 2012
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