Fast and Privacy-Preserving Spatial Keyword Authorization Query with access control

Abstract

In light of the accelerated advancement of GPS and the explosive growth of data, outsourcing spatial data to cloud servers has become a common practice for location-based service providers to alleviate computational and storage burdens. However, existing spatial keyword query schemes with fine-grained access control often rely on additional encryption techniques, such as homomorphic encryption and RSA, for spatial range queries, resulting in significant computational overhead. Furthermore, most schemes enforce access policies on all index tree nodes, which compromises efficiency and practicality. To address these challenges, we propose the Fast and Privacy-Preserving Spatial Keyword Authorization Query (FPAQ) scheme. FPAQ leverages Geohash and Quadtree to construct an index tree, achieving sub-linear search complexity and efficient spatial keyword queries. And introduces a novel authorization mechanism based on secret keys, embedding authorization information in non-leaf nodes to minimize computational overhead, while access policies are enforced only on leaf nodes. Additionally, attribute-based encryption is employed to support fine-grained access control in multi-user scenarios. Formal security analysis confirms that FPAQ safeguards data confidentiality and query privacy. Experimental results on the Yelp dataset validate the scheme’s superior efficiency and scalability compared to existing methods.