Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

7-2020

Abstract

With the increasing popularity of geo-positioning technologies and mobile Internet, spatial keyword data services have attracted growing interest from both the industrial and academic communities in recent years. Meanwhile, a massive amount of data is increasingly being outsourced to cloud in the encrypted form for enjoying the advantages of cloud computing while without compromising data privacy. Most existing works primarily focus on the privacy-preserving schemes for either spatial or keyword queries, and they cannot be directly applied to solve the spatial keyword query problem over encrypted data. In this paper, we study the challenging problem of Privacy-preserving Boolean Range Query (PBRQ) over encrypted spatial databases. In particular, we propose two novel PBRQ schemes. Firstly, we present a scheme with linear search complexity based on the space-filling curve code and Symmetric-key Hidden Vector Encryption (SHVE). Then, we use tree structures to achieve faster-than-linear search complexity. Thorough security analysis shows that data security and query privacy can be guaranteed during the query process. Experimental results using real-world datasets show that the proposed schemes are efficient and feasible for practical applications, which is at least ×70 faster than existing techniques in the literature.

Keywords

Privacy-preserving, Boolean range queries, Encrypted spatial data

Discipline

Information Security

Research Areas

Cybersecurity

Publication

2020 38th IEEE Conference on Computer Communications, INFOCOM: Toronto, Canada; July 6-9: Proceedings

First Page

2253

Last Page

2262

ISBN

9781728164120

Identifier

10.1109/INFOCOM41043.2020.9155505

Publisher

IEEE

City or Country

Piscataway, NJ

Embargo Period

5-10-2021

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/INFOCOM41043.2020.9155505

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