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Rphx: Result Pattern Hiding Conjunctive Query over Private Compressed Index Using Intel SGX

  • Qin Jiang
  • , Ee Chien Chang
  • , Yong Qi
  • , Saiyu Qi
  • , Pengfei Wu
  • , Jianfeng Wang
  • Xi'an Jiaotong University
  • National University of Singapore
  • Xidian University

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Deploying data storage and query service in an untrusted cloud server raises critical privacy and security concerns. This paper focuses on the fundamental problem of processing conjunctive keyword queries over an untrusted cloud in a privacy-preserving manner. Previous tree-based searchable symmetric encryption (SSE) schemes, such as IBTree and VBTree, can process conjunctive keyword queries in a secure and efficient way. However, these schemes cannot address 'Result Pattern (RP)' leakage, which can be used to recover the keywords contained in a conjunctive keyword query. To combat this challenging problem, we propose a result pattern hiding conjunctive query scheme named Rphx using Intel SGX. In particular, we first propose a new 'SGX-aware' compressed index named VIBT by combining variable-length bloom filter tree, matryoshka filter and online cipher. To achieve RP hiding, we then introduce a new tree-based SSE scheme named Rphx by deploying VIBT to Intel SGX. Security analysis shows that Rphx can enhance the security requirements by hiding RP leakage under the IND-CKA2 security model. Experimental results show that VIBT gains at least 30× improvement in storage efficiency and Rphx can achieve comparable search efficiency comparing with previous works.

Original languageEnglish
Pages (from-to)1053-1068
Number of pages16
JournalIEEE Transactions on Information Forensics and Security
Volume17
DOIs
StatePublished - 2022

Keywords

  • Intel SGX
  • Private conjunctive queries
  • SSE
  • result pattern

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