Trace your footprint: Efficient spatial keyword query over encrypted trajectory data

Publication Type

Journal Article

Publication Date

10-2025

Abstract

With the popularity of mobile devices, spatial-textual trajectory query has been deployed in applications such as trajectory-based navigation and travel route recommendation. Massive trajectory data have been outsourced to cloud servers for storage and sharing such as spatial keyword search. However, existing solutions only support similarity queries in the spatial dimension and still incur high storage and query costs, which cannot scale well in large-scale trajectory data scenarios. To solve the above issues, we first achieve an Efficient Range Query over Encrypted Trajectory Data (ERT) using Douglas-Peucker trajectory compression algorithm, random matrix multiplication, filtering-verification mechanism and polynomial fitting technology. Then, we further propose an enhanced Efficient Spatial Keyword Query over Encrypted Trajectory Data (ESKT) by constructing a unified spatial-textual index structure, which can find relevant trajectories that are within some arbitrary geometric range and contain all query keywords. Finally, we formally prove that our schemes are secure against chosen-plaintext-attack, and conduct extensive experiments to demonstrate that our schemes improve the query efficiency by almost 100× when compared with state-of-the-art solutions.

Keywords

Trajectory query, spatial keyword query, trajectory compression, filtering-verification mechanism, spatial-textual index structure

Discipline

Information Security

Research Areas

Cybersecurity

Publication

IEEE Transactions on Information Forensics and Security

Volume

20

First Page

11936

Last Page

11949

ISSN

1556-6013

Identifier

10.1109/TIFS.2025.3624950

Publisher

Institute of Electrical and Electronics Engineers

Additional URL

https://doi.org/10.1109/TIFS.2025.3624950

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