| 引用本文： |
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周凯,陈福,江航宇,曹怀虎,朱建明.面向可信数据空间的数据要素多链交易方法[J].信息安全学报,已采用 [点击复制]
- ZHOU KAI,chenfu,jianghangyu,caohuaihu,zhujianming.A Multi-Chain Data Element Trading Method for Trusted Data Spaces[J].Journal of Cyber Security,Accept [点击复制]
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| 摘要: |
| 针对可信数据空间中数据要素交易存在的交易可信执行能力不足、履约行为约束困难、收益分配缺乏客观依据以及区块链链上检索效率低等问题，提出一种基于区块链的面向可信数据空间的数据要素多链交易方法。该方法构建了由供应链、需求链和交易链组成的联盟链多链协同架构，并结合链下数据索引技术，实现订单元数据、交易状态和历史记录的分层链上链下存储与协同管理。在此基础上，设计了离散竞价与贪心匹配相结合的智能合约订单撮合算法，建立了信誉更新与违约惩罚模型，并引入基于Shapley值法的服务费分摊机制，实现交易匹配、履约监管和收益协调的一体化处理。进一步地，基于国产开源联盟链FISCO BCOS和智能合约编程语言Solidity实现交易发布、自动匹配、信誉约束、违约处理、交易结算及查询审计等关键流程。实验结果表明，所提方法在多种供需拓扑配置下均能够保持较高的交易匹配度。与时间优先撮合、双向拍卖基线和信誉匹配基线相比，本文方法在交易匹配度和违约行为约束度方面均具有更优表现；消融实验进一步表明，离散竞价排序、信誉准入以及信誉更新与违约惩罚机制对提升撮合效率和降低平均履约偏差率具有重要作用。同时，多链协同与链下索引机制能够提升链上交易信息查询效率。 |
| 关键词: 可信数据空间 数据要素交易 多链架构 智能合约 信誉评估 Shapley值 |
| DOI： |
| 投稿时间：2026-05-10修订日期：2026-09-26 |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| A Multi-Chain Data Element Trading Method for Trusted Data Spaces |
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ZHOU KAI, chenfu, jianghangyu, caohuaihu, zhujianming
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| (School of Information, Central University of Finance and Economics) |
| Abstract: |
| To address the problems of insufficient trustworthy execution, weak constraints on contract fulfillment, lack of an objective basis for benefit allocation, and low on-chain retrieval efficiency in data element trading within trusted data spaces, this paper proposes a blockchain-based multi-chain trading method for data elements in trusted data spaces. The proposed method constructs a consortium blockchain-based collaborative multi-chain architecture consisting of a supply chain, a demand chain, and a transaction chain. By incorporating an off-chain data indexing mechanism, it enables hierarchical on-chain/off-chain storage and collaborative management of order metadata, transaction states, and historical records. On this basis, a smart contract-based order matching algorithm combining discrete bidding and greedy matching is designed; a reputation update and breach penalty model is established; and a service fee allocation mechanism based on the Shapley value is introduced, thereby achieving integrated processing of transaction matching, contract fulfillment supervision, and benefit coordination. Fur-thermore, key processes, including transaction publishing, automatic matching, reputation-based constraint enforcement, breach handling, transaction settlement, and query auditing, are implemented using the domestic open-source consortium blockchain platform FISCO BCOS and the Solidity smart contract programming language. Experimental results show that the proposed method maintains a high transaction matching degree under multiple supply-demand topology configurations. Compared with the time-priority matching mechanism, the double-auction baseline, and the reputation-based matching baseline, the proposed method achieves better performance in both transaction matching degree and breach behavior constraint degree. Ablation experiments further demonstrate that discrete bidding-based sorting, reputation admission control, and the reputation update and breach penalty mechanism play important roles in improving matching efficiency and reducing the average fulfillment deviation rate. Meanwhile, the multi-chain collaboration and off-chain indexing mechanism improves the efficiency of on-chain transaction information retrieval. |
| Key words: trusted data spaces, data element trading, multi-chain architecture, smart contracts, reputation evaluation, Shapley value |
