DMPSI: Efficient Scalable Delegated Multiparty PSI and PSI-CA with Oblivious PRF

Yihao Yang, Yunbo Yang*, Xiang Chen, Xiaolei Dong*, Zhenfu Cao, Jiachen Shen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Multiparty private set intersection (PSI) allows several parties, each holding a set of elements, to jointly compute the intersection without leaking any additional information. With the development of cloud computing, delegating the computation to an untrsuted cloud server is becoming a major problem, where the untrusted cloud server may try to get some sensitive information from clients' private information. However, it is complex to build an efficient and reliable scheme to protect user privacy. In order to overcome this problem, we propose DMPSI, an efficient delegated PSI (with cardinality) protocol in a multiparty setting. DMPSI avoids using heavy cryptographic primitives (mainly rely on symmetric-key encryption) to achieve better performance. In addition, both PSI and PSI with the cardinality of DMPSI are secure against semi-honest adversaries and allow any number of colluding clients (at least one honest client). We do experiments to compare the proposed DMPSI with some state-of-the-art works to evaluate overall performance. In addition, we also compare the proposed Oks-PRF with some state-of-the-art multi-point OPRF to highlight our efficiency. The experimental results show that proposed both Oks-PRF and DMPSI(-CA) has better performance and is scalable in the number of clients and the set size.

Original languageEnglish
Pages (from-to)497-508
Number of pages12
JournalIEEE Transactions on Services Computing
Volume17
Issue number2
DOIs
StatePublished - 1 Mar 2024

Keywords

  • Private set intersection
  • multiparty computation
  • oblivious pesudorandom function

Fingerprint

Dive into the research topics of 'DMPSI: Efficient Scalable Delegated Multiparty PSI and PSI-CA with Oblivious PRF'. Together they form a unique fingerprint.

Cite this