Paper Info
Title
Search Me in the Dark: Privacy-preserving Boolean Range Query over Encrypted Spatial Data
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.
Year
DOI
Venue
2020
10.1109/INFOCOM41043.2020.9155505
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
Keywords
DocType
ISSN
privacy-preserving,Boolean range queries,encrypted spatial data
Conference
0743-166X
ISBN
Citations 
PageRank 
978-1-7281-6413-7
1
0.36
References 
Authors
0
7
Name
Order
Citations
PageRank
Xiangyu Wang17015.17
Jianfeng Ma2529.23
Ximeng Liu313531.84
R.H Deng44423362.82
Yinbin Miao513618.45
Dan Zhu621.40
Zhuoran Ma793.18