MDPPC: Efficient Scalable Multiparty Delegated PSI and PSI Cardinality

  • Yihao Yang
  • , Xiaolei Dong*
  • , Jiachen Shen*
  • , Zhenfu Cao
  • , Yunbo Yang
  • , Jun Zhou
  • , Liming Fang
  • , Zhe Liu
  • , Chunpeng Ge
  • , Chunhua Su
  • , Zongyang Hou
  • *Corresponding author for this work

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

3 Scopus citations

Abstract

Private Set Intersection (PSI) is one of the most important functions in secure multiparty computation (MPC). PSI protocols have been a practical cryptographic primitive and there are many privacy-preserving applications based on PSI protocols such as computing conversion of advertising and distributed computation. Private Set Intersection Cardinality (PSI-CA) is a useful variant of PSI protocol. PSI and PSI-CA allow several parties, each holding a private set, to jointly compute the intersection and cardinality, respectively without leaking any additional information. Nowadays, most PSI protocols mainly focus on two-party settings, while in multiparty settings, parties are able to share more valuable information and thus more desirable. On the other hand, with the advent of cloud computing, delegating computation to an untrusted server becomes an interesting problem. However, most existing delegated PSI protocols are unable to efficiently scale to multiple clients. In order to solve these problems, this paper proposes MDPPC, an efficient PSI protocol which supports scalable multiparty delegated PSI and PSI-CA operations. Security analysis shows that MDPPC is secure against semi-honest adversaries and it allows any number of colluding clients. For 15 parties with set size of 220 on server side and 216 on clients side, MDPPC costs only 81 seconds in PSI and 80 seconds in PSI-CA, respectively. The experimental results show that MDPPC has high scalability.

Original languageEnglish
Title of host publication2023 20th Annual International Conference on Privacy, Security and Trust, PST 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350313871
DOIs
StatePublished - 2023
Event20th Annual International Conference on Privacy, Security and Trust, PST 2023 - Hybrid, Copenhagen, Denmark
Duration: 21 Aug 202323 Aug 2023

Publication series

Name2023 20th Annual International Conference on Privacy, Security and Trust, PST 2023

Conference

Conference20th Annual International Conference on Privacy, Security and Trust, PST 2023
Country/TerritoryDenmark
CityHybrid, Copenhagen
Period21/08/2323/08/23

Keywords

  • Multiparty Computation
  • Oblivious Pseudorandom Function
  • Private Set Intersection

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