Oblivious and Privacy-Preserving IoT Spatial Range Keyword Query With Dynamic Authorization
Year: 2026
Type: article
Abstract: With the rapid development of the Internet of Things (IoT), large-scale spatial data are generated and outsourced to cloud servers, which promotes the demand for privacy-preserving spatial range keyword query. However, existing query schemes usually fail to simultaneously support fine-grained access control, oblivious retrieval, suppression of pattern leakage, and forward/backward security. In this paper, we propose OA-SRKQ, an Oblivious with dynamic Authorization for Spatial Range Keyword Query scheme that supports fine-grained access control over query regions and user attributes, while also considering pattern leakage and forward/backward security. Technically, for privacy-preserving range keyword query over outsourced spatial IoT data, we introduce Spatial-Keyword Pseudo-Random Function (SK-PRF) to process spatial keyword data, Spatial-Attribute Authorization (SA-Auth) to achieve fine-grained authorization based on locations and user attributes, and Response-Protection (RP) to achieve result pattern hiding. We also provide a security analysis of OA-SRKQ. Finally, we conduct extensive experiments and evaluate the performance of existing solutions and OA-SRKQ on a real-world dataset. The results demonstrate the practical computation and communication overhead of spatial range keyword search. In particular, OA-SRKQ outperforms state-of-the-art schemes with about 69% search-time reduction and still achieves 23.45% lower search time than OEKA on datasets with #record=10000.
Source: IEEE Internet of Things Journal
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W7204936609