Verifiable location range query in multi-source outsourced database

Ruyu Yan (), Ruirui Gao (), Ke Huang (), Haolin Wang (), Yun Zhao () and Xiong Li ()
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Ruyu Yan: University of Electronic Science and Technology of China
Ruirui Gao: University of Electronic Science and Technology of China
Ke Huang: University of Electronic Science and Technology of China
Haolin Wang: Electric Power Research Institute of CSG
Yun Zhao: Electric Power Research Institute of CSG
Xiong Li: University of Electronic Science and Technology of China

Telecommunication Systems: Modelling, Analysis, Design and Management, 2025, vol. 88, issue 2, No 16, 12 pages

Abstract: Abstract With the rapid advancement of big data technologies, Location-Based Services have significantly enhanced user convenience while simultaneously exacerbating the challenge of data explosion. The advent of cloud computing has alleviated issues related to data silos and information overload, thereby facilitating the comprehensive realization of data value. However, given that cloud servers cannot be considered fully trustworthy, malicious servers may potentially execute unauthorized queries, return falsified or manipulated query results, or compromise user query privacy. In this paper, we propose a Secure and Verifiable Location Range Query (SVLRQ) scheme that enables users to perform secure and efficient range queries on location data while maintaining the capability to verify query results. Specifically, the SVLRQ scheme introduces Order-Revealing Encryption for location information encryption and constructs a pyramid hash tree data structure to ensure both verifiability and privacy preservation. Our SVLRQ scheme achieves security, verifiability, and privacy preservation compared to existing solutions. We provide rigorous theoretical analysis and formal proofs regarding the scheme’s security and correctness. Experimental results demonstrate the scheme’s strong practical applicability. Notably, when operating on a database of size $$2\times 10^5$$ 2 × 10 5 , the query time of existing solutions (2.32 ms and 0.38 ms) is approximately 116 times and 19 times greater, respectively, than that of our proposed scheme (0.02 ms).

Keywords: Cloud computing; Verifiable range query; Location-based service (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11235-025-01288-w

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