Updatable Private Set Intersection with Forward Privacy

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Private set intersection (PSI) facilitates the computation of intersection between the private sets of two parties, ensuring that no additional information beyond the intersection itself is revealed. However, most state-of-the-art are limited to static PSI, leaving updatable PSI untouched. Existing PSI protocols will cost huge computational resources to compute intersection on updated sets. More seriously, none of the existing updatable PSI approaches can achieve both secure addition and deletion operations in once update. To address these challenges, we propose Forward Private Updatable PSI (FUPSI) for two-party setting. FUPSI is designed to support addition and deletion simultaneously, while ensuring forward privacy against semi-honest adversaries. In this work, we analyze the infeasibility of secure synchronous addition and deletion in the existing updatable PSI approaches, by presenting a practical attack which would lead to privacy leakages while deletion function is performed. Then, to resist this attack against semi-honest adversaries, we demonstrate how FUPSI can protect the forward privacy of user sets, by utilizing a variant of keyword Private Information Retrieval (PIR) to hide sensitive intermediate parameters. Specifically in FUPSI, two parties execute keyword PIR to retrieve a flag indicating that the current element is added or deleted so as to determine whether it is in the participants' datasets. Finally, we provide the formal security proof for our proposed FUPSI, and extensive experimental results demonstrate efficiency and the practicality of our proposal. For instance, the communication complexity of our proposal is only logarithmically related to the size of update sets and the computational overhead is mainly composed of logarithmical times PIR calculations. Owing to the variant of keyword PIR, our work also incurs minimal communication overhead even for enormous datasets, which performs well in updatable settings and slow networks.

Original languageEnglish
Pages (from-to)8573-8586
Number of pages14
JournalIEEE Transactions on Information Forensics and Security
Volume19
DOIs
StatePublished - 2024

Keywords

  • Private set intersection
  • forward privacy
  • keyword private information retrieval
  • updatable PSI

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