Cross-lingual multi-keyword rank search with semantic extension over encrypted data

Zhitao Guan, Xueyan Liu, Longfei Wu, Jun Wu, Ruzhi Xu, Jinhu Zhang, Yuanzhang Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

71 Citations (Scopus)

Abstract

The emergence of searchable encryption technology sheds new light on the problem of secure search over encrypted data, which has been a research hotspot in the past few years. However, most existing search schemes based on searchable encryption only support queries in a certain language. The few searchable encryption schemes that have implemented multilingual search fail to achieve automated cross-lingual retrieval, which significantly impacts users search experience. Additionally, most of these schemes only support the exact matching and can-not provide semantic search. Hence, the implementation of cross-lingual and semantic search together remains an open topic for searchable encryption. To the best of our knowledge, no previous research has investigated the problem of cross-lingual ranked search over encrypted cloud data. To address this issue, we propose a cross-lingual multi-keyword rank search (CLRSE) scheme upon the Open Multilingual Wordnet. Our CLRSE scheme can break the barrier of languages, and realizes intelligent and personalized search through flexible keyword and language preference settings. Additionally, an improved scheme is developed to speed up the sorting process. We evaluate the performance of our scheme including security, functionality, precision, and efficiency, with extensive experiments.

Original languageEnglish
Pages (from-to)523-540
Number of pages18
JournalInformation Sciences
Volume514
DOIs
Publication statusPublished - Apr 2020

Keywords

  • Cloud computing
  • Privacy-preserving
  • Searchable encryption
  • Semantic search
  • Top-k

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Guan, Z., Liu, X., Wu, L., Wu, J., Xu, R., Zhang, J., & Li, Y. (2020). Cross-lingual multi-keyword rank search with semantic extension over encrypted data. Information Sciences, 514, 523-540. https://doi.org/10.1016/j.ins.2019.11.013