Privacy-Preserving Ranked Multi-keyword Fuzzy Search on Cloud Encrypted Data Supporting Range Query

Abstract

It is a desirable technique for cloud users to make the fullest use of cloud encrypted data by searching what they need through input keywords. Exact keyword search schemes over encrypted data have been well tackled for better retrieval efficiency and accuracy. However, existing researches on fuzzy keyword search are mainly based on single-input keyword, where multi-keyword fuzzy search remains to be unsolved, and keyword-based search application expansion, i.e., range query based on fuzzy search, has not yet proposed. In this paper, for the first time, we propose a novel ranked multi-keyword fuzzy search scheme supporting range query called RMFSSRQ by exploiting order-preserving encryption and locality-sensitive hashing. Our scheme achieves ranked fuzzy keyword matching by algorithmic design to support retrieval ranking of returned encrypted files. It can also conduct fuzzy search without pre-defined keyword dictionary restraints and eliminate increasing computation and search overheads of multi-keyword fuzzy search compared with traditional fuzzy keyword search schemes. As an expansion of our scheme's application, range query can be achieved by building secure per file Bloom Filter (BF) index. So, the scheme can achieve ranked multi-keyword fuzzy search as well as range query on cloud encrypted data through twolayered BFs per document. Extensive security analysis and experimental results on real-world data set show that our proposed scheme can securely reach the design goals for B Jie Wang keyword search on encrypted data. To the best of our knowledge, this is the first try to achieve ranking of retrieval results and range query based on fuzzy search over cloud encrypted data.

EliMFS: Achieving Efficient, Leakage-Resilient, and Multi-Keyword Fuzzy Search on Encrypted Cloud Data

“…Therefore, its performance may be severely influenced when there are huge file sets to search. In [44], Wang et al proposed a ranked multi-keyword fuzzy search on encrypted data based on a two-layered index structure. Unfortunately, both of the two layers use forward index, which is still linear with the file set size in the cloud.…”

A Privacy-Preserving Multi-Keyword Ranked Search Over Encrypted Data in Hybrid Clouds

“…To achieve fuzzy search, the locality-sensitive hashing functions [23], wordnet and secure KNN are adopted. Wang et al [16] presented a multi-keyword fuzzy search scheme which supports range queries by adopting the locality-sensitive hashing functions, bloom filtering [24] and order-preserving encryption. Fu et al [17] proposed a synonym expansion of document keywords and realized the synonym-based multi-keyword ranked search scheme.…”

Privacy-preserving Content-aware Search based on Two-level Index

“…Fu et al [Fu, Shu and Wang (2015)] proposed similarity search scheme for encrypted documents based on simhash. Wang et al [Wang, Yu and Zhao (2015)] proposed a fuzzy search based on multi-keywords for achieving range query using a sequence reservation encryption and two-layer Bloom. Huang et al [Huang, Fu and Sun (2016)] combined gene sequences with secure searchable indexes to propose a secure searchable encryption scheme.…”