Literature DB >> 33266523

Two-Party Privacy-Preserving Set Intersection with FHE.

Yunlu Cai1, Chunming Tang1,2, Qiuxia Xu3.   

Abstract

A two-party private set intersection allows two parties, the client and the server, to compute an intersection over their private sets, without revealing any information beyond the intersecting elements. We present a novel private set intersection protocol based on Shuhong Gao's fully homomorphic encryption scheme and prove the security of the protocol in the semi-honest model. We also present a variant of the protocol which is a completely novel construction for computing the intersection based on Bloom filter and fully homomorphic encryption, and the protocol's complexity is independent of the set size of the client. The security of the protocols relies on the learning with errors and ring learning with error problems. Furthermore, in the cloud with malicious adversaries, the computation of the private set intersection can be outsourced to the cloud service provider without revealing any private information.

Entities:  

Keywords:  fully homomorphic encryption; privacy-preserving; private set intersection; secure multiparty computation

Year:  2020        PMID: 33266523     DOI: 10.3390/e22121339

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  1 in total

1.  Towards Secure Big Data Analysis via Fully Homomorphic Encryption Algorithms.

Authors:  Rafik Hamza; Alzubair Hassan; Awad Ali; Mohammed Bakri Bashir; Samar M Alqhtani; Tawfeeg Mohmmed Tawfeeg; Adil Yousif
Journal:  Entropy (Basel)       Date:  2022-04-06       Impact factor: 2.738

  1 in total

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