Privacy-Preserving Dynamic Spatial Keyword Query Scheme with Multi-Attribute Cost Constraints in Cloud–Edge Collaboration
Zhenya Chen, Yushen Deng, Ming Yang, Xiaoming Wu, Xin Wang, Peng Wei · Electronics · 2025
The rapid advancement of the Internet of Things (IoT) and mobile devices has made location-based services (LBSs) increasingly prevalent, significantly improving daily convenience and work efficiency. However, this widespread usage has raised growing concerns about privacy and security, particularly during data outsourcing to cloud servers, where users’ location information and related data are susceptible to breaches by malicious actors or attackers. Traditional privacy-preserving spatial keyword schemes often employ Bloom filters for data encoding and storage. While Bloom filters offer high lookup speeds, they suffer from limitations such as a relatively high false positive rate in certain scenarios and poor space efficiency. These issues can adversely affect query accuracy and overall user experience. Furthermore, existing schemes have not sufficiently addressed the multi-attribute characteristics of spatial textual data. At the same time, relying solely on cloud servers for large-scale data processing introduces additional challenges, including heavy computational overhead, high latency, and substantial communication costs. To address these challenges, we propose a cloud–edge collaborative privacy-preserving dynamic spatial keyword query scheme with multi-attribute cost constraints. This scheme introduces a novel index structure that leverages security-enhanced Xor filter technology and Geohash techniques. This index structure not only strengthens query security and efficiency but also significantly reduces the false positive rate, thereby improving query accuracy. Moreover, the proposed scheme supports multi-attribute cost constraints and dynamic data updates, allowing it to adapt flexibly to practical requirements and user-specific needs. Finally, through security analysis and experimental evaluation, we demonstrate that the proposed scheme is both secure and effective.