File(s) under permanent embargo

When geo-text meets security: privacy-preserving boolean spatial keyword queries

conference contribution
posted on 2019-01-01, 00:00 authored by N Cui, Jianxin LiJianxin Li, X Yang, B Wang, M Reynolds, Yong XiangYong Xiang
In recent years, spatial keyword query has attracted wide-spread research attention due to the popularity of the location-based services. To efficiently support the online spatial keyword query processing, the data owners need to outsource their data and the query processing service to cloud platforms. However, the outsourcing services may raise privacy leaking issues because the cloud server on the platforms may not be trusted for both data owners and query users. Therefore, in this work, we first propose and formalize the problem of privacy-preserving boolean spatial keyword query under the widely accepted Known Background Thread Model. And then, we devise a novel privacy-preserving spatial-textual Bloom Filter encoding structure and an encrypted R-tree index. They can maintain both spatial and text information together in a secure way while answering the encrypted spatial keyword queries without the need for data decryption. To further accelerate the query processing, a compressed encrypted index is provided to deal with the challenges of the large dimension expansion and the expensive space consumption in the encrypted R-tree index. In addition, we develop the corresponding algorithms based on the designed index, and present the in-depth security analysis to show our work's satisfaction meeting the strong secure scheme. Finally, we demonstrate the performance of our proposed index and algorithms by conducting extensive experiments on four datasets under various system settings.

History

Event

IEEE Computer Society. Conference (35th : 2019 : Macao, China)

Series

IEEE Computer Society Conference

Pagination

1046 - 1057

Publisher

Institute of Electrical and Electronics Engineers

Location

Macao, China

Place of publication

Piscataway, N.J.

Start date

2019-04-08

End date

2019-04-11

ISSN

1084-4627

ISBN-13

9781538674741

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2019, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICDE 2019 : Proceedings of the 2019 IEEE 35th International Conference on Data Engineering