Comprehensive survey on privacy-preserving spatial data query in transportation systems

Publication Type

Journal Article

Publication Date

12-2023

Abstract

With the rapid development of Intelligent Transportation System (ITS), a large number of spatial data are generated in ITS. Although outsourcing spatial data to the cloud server can reduce the high local computation and storage overheads, it will also lead to security and privacy issues. Therefore, it is necessary to have a survey to specifically summarize these advanced privacy-preserving spatial data query schemes. However, the existing surveys considering both location information and keywords of spatial data only summarize the spatial keyword query scheme in plaintext environment, they do not consider the privacy of spatial data. Although there are some surveys on privacy-preserving spatial data query, they only focus on the location information of spatial data without considering descriptive keywords. Therefore, to understand the progress and research trends in the field, we give a comprehensive survey on secure spatial data query in ITS to summarize and analyze the most advanced solutions. Then, we make a comprehensive and detailed comparison of existing solutions in terms of query function, index structure, time complexity, security, etc. Finally, we show some open challenges and potential research directions for privacy-preserving spatial data query.

Keywords

Spatial data, privacy leakage, location and keywords, spatial data query

Discipline

Information Security | Numerical Analysis and Scientific Computing | Transportation

Research Areas

Cybersecurity

Publication

IEEE Transactions on Intelligent Transportation Systems

Volume

242

Issue

12

First Page

13603

Last Page

13616

ISSN

1524-9050

Identifier

10.1109/TITS.2023.3295798

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TITS.2023.3295798

Link to Full Text

Share

COinS