区块链上具有丰富查询能力和低存储冗余的可验证查询方案

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Linkun Sun , Luqi Wang , Wenbao Jiang, Yangnan Guo
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引用次数: 0

摘要

在当前的区块链可验证查询研究中,为了实现高效且特征丰富的查询算法,通常需要对要索引的数据进行冗余存储。然而,目前大多数区块链都面临着数据快速增长的问题,导致节点大量消耗存储资源。为了在减少节点存储负担的同时提供高效通用的可验证查询能力,提出了一种基于密码累加器的可验证通用查询方案。通过巧妙地建立密码积累值与元素成员证明之间的逻辑关系,有效地减少了链上数据结构的冗余设计。在此基础上,设计了过滤器聚合算法、块间索引结构和范围查询方法,将数值属性比较问题转化为集合中成员的存在性证明问题。安全性分析和实验分析验证了该方法的鲁棒性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A verifiable query scheme with rich query capabilities and low storage redundancy on blockchain
In current blockchain verifiable query research, redundant storage of data to be indexed is often required to enable efficient and feature-rich query algorithms. However, most blockchains currently face the problem of rapid data growth, leading to significant storage resource consumption by nodes. To provide a high-efficiency and generic verifiable query capability while reducing the storage burden on nodes, we propose a cryptographic accumulator-based verifiable generic query scheme. By skilfully establishing a logical relationship between the cryptographic accumulation value and the proof of element members, our scheme effectively reduces the redundant design of data structures on the chain. Additionally, we design a filter aggregation algorithm, an inter-block indexing structure, and a range query method that transforms the numerical attribute comparison problem into a proof-of-existence problem for members in a collection based on this scheme. Security analysis and experimental analysis verify the robustness and practicality of the proposed techniques.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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