Optimized unified query verification scheme for cloud database services

To address the significant overhead in cloud database query verification schemes when handling diverse data types, as well as the inefficiencies caused by complex authentication data structures during the generation of verification objects, an optimized unified query verification scheme was proposed. The query attributes were conbertdy by the proposed scheme into sets, extending this approaching to support range-based numerical queries. By utilizing a prefix binary tree, multi-dimensional range numerical queries and other data types were uniformly mapped to Boolean queries. Additionally, an Authenticated Data Structure (ADS) based on Merkle Hash Trees (MHT) was designed to verify query integrity using the lowest common ancestor, effectively reducing the size of the verification object. Redis was employed as a middleware to serve as an inmemory cache for hot data in cloud databases, reducing both network load and computational overhead. Simulation experiments, conducted with identical request sizes, demonstrate that the optimized unified query verification scheme maintains constant verification times for single queries, regardless of data size. Moreover, compared to existing cloud database query verification schemes, the proposed scheme achieves a 12% reduction in overall response time for queries with set attributes, a 38% reduction in average response time for range-based numerical queries, and a 14% reduction in average response time for queries involving diverse data types.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/isaeece66033.2025.11159866
Primary Topic
Cloud Data Security Solutions
Type
article
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article

Optimized unified query verification scheme for cloud database services

Sicheng Zhang, Xiuxia Tian
Cloud Data Security Solutions
article

Optimized unified query verification scheme for cloud database services

Sicheng Zhang, Xiuxia Tian
article en

Abstract

To address the significant overhead in cloud database query verification schemes when handling diverse data types, as well as the inefficiencies caused by complex authentication data structures during the generation of verification objects, an optimized unified query verification scheme was proposed. The query attributes were conbertdy by the proposed scheme into sets, extending this approaching to support range-based numerical queries. By utilizing a prefix binary tree, multi-dimensional range numerical queries and other data types were uniformly mapped to Boolean queries. Additionally, an Authenticated Data Structure (ADS) based on Merkle Hash Trees (MHT) was designed to verify query integrity using the lowest common ancestor, effectively reducing the size of the verification object. Redis was employed as a middleware to serve as an inmemory cache for hot data in cloud databases, reducing both network load and computational overhead. Simulation experiments, conducted with identical request sizes, demonstrate that the optimized unified query verification scheme maintains constant verification times for single queries, regardless of data size. Moreover, compared to existing cloud database query verification schemes, the proposed scheme achieves a 12% reduction in overall response time for queries with set attributes, a 38% reduction in average response time for range-based numerical queries, and a 14% reduction in average response time for queries involving diverse data types.

Shanghai University of Electric Power (CN)
Openalex Percentile: Top 62%
Cloud Data Security Solutions
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