Efficient Strong Privacy-Preserving Conjunctive Keyword Search Over Encrypted Cloud Data

Chang Xu*, Ruijuan Wang, Liehuang Zhu, Chuan Zhang, Rongxing Lu, Kashif Sharif

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Searchable symmetric encryption (SSE) supports keyword search over outsourced symmetrically encrypted data. Dynamic searchable symmetric encryption (DSSE), a variant of SSE, further enables data updating. Most DSSE works with conjunctive keyword search primarily consider forward and backward privacy. Ideally, the server should only learn the result sets involving all keywords in the conjunction. However, existing schemes suffer from keyword pair result pattern (KPRP) leakage, revealing the partial result sets containing two of query keywords. We propose the first DSSE scheme to address aforementioned concerns that achieves strong privacy-preserving conjunctive keyword search. Specifically, our scheme can maintain forward and backward privacy and eliminate KPRP leakage, offering a higher level of security. The search complexity scales with the number of documents stored in the database in several existing schemes. However, the complexity of our scheme scales with the update frequency of the least frequent keyword in the conjunction, which is much smaller than the size of the entire database. Besides, we devise a least frequent keyword acquisition protocol to reduce frequent interactions between clients. Finally, we analyze the security of our scheme and evaluate its performance theoretically and experimentally. The results show that our scheme has strong privacy preservation and efficiency.

Original languageEnglish
Pages (from-to)805-817
Number of pages13
JournalIEEE Transactions on Big Data
Volume9
Issue number3
DOIs
Publication statusPublished - 1 Jun 2023

Keywords

  • DSSE
  • Strong privacy-preserving
  • conjunctive keyword search

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