Privacy-preserving multi-keyword ranked search over encrypted cloud data

Ning Cao, Cong Wang, Ming Li, Kui Ren, Wenjing Lou

Research output: Contribution to journalArticlepeer-review

752 Scopus citations

Abstract

With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data have to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted data in cloud computing (MRSE). We establish a set of strict privacy requirements for such a secure cloud data utilization system. Among various multi-keyword semantics, we choose the efficient similarity measure of "coordinate matching," i.e., as many matches as possible, to capture the relevance of data documents to the search query. We further use "inner product similarity" to quantitatively evaluate such similarity measure. We first propose a basic idea for the MRSE based on secure inner product computation, and then give two significantly improved MRSE schemes to achieve various stringent privacy requirements in two different threat models. To improve search experience of the data search service, we further extend these two schemes to support more search semantics. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given. Experiments on the real-world data set further show proposed schemes indeed introduce low overhead on computation and communication.

Original languageEnglish (US)
Article number6674958
Pages (from-to)222-233
Number of pages12
JournalIEEE Transactions on Parallel and Distributed Systems
Volume25
Issue number1
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Keywords

  • Cloud computing
  • keyword search
  • privacy-preserving
  • ranked search
  • searchable encryption

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

Fingerprint

Dive into the research topics of 'Privacy-preserving multi-keyword ranked search over encrypted cloud data'. Together they form a unique fingerprint.

Cite this