Trace Your Footprint: Efficient Spatial Keyword Query Over Encrypted Trajectory Data

doi:10.1109/TIFS.2025.3624950

Trace Your Footprint: Efficient Spatial Keyword Query Over Encrypted Trajectory Data

2025-01-01

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Kim‐Kwang Raymond Choo

R

Robert H. Deng

DOI：10.1109/TIFS.2025.3624950

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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 ( $\textsf {ERT}$ ) 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 ( $\textsf {ESKT}$ ) 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\times $ when compared with state-of-the-art solutions.

Keywords:

Trajectory query

spatial keyword query

trajectory compression

filtering-verification mechanism

spatial-textual index structure

Trace Your Footprint: Efficient Spatial Keyword Query Over Encrypted Trajectory Data

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