基于侧链的水产品跨链交易模型研究

Cross-chain Trading Model of Aquatic Products Based on Side Chain

摘要:

跨链技术解决了水产品供应链各企业区块链之间的信息孤岛问题，但是在跨链交易过程中存在着隐私泄露的风险。为了提高水产品跨链交易的安全性和隐私性，基于水产品交易业务流程，在常用跨链技术的基础上，提出了基于侧链的水产品跨链交易模型。模型设计了主链和侧链资产互操作流程，用智能合约实现主链和侧链资产的双向锚定；基于水产品跨链交易的业务特点设计跨链数据的数据结构和跨链交易流程；使用三阶段提交协议保证跨链交易的数据一致性，提高交易成功率，完善交易失败时的处理流程；同时，针对侧链有可能带来的双花问题，采用监听方式加以控制。最后，基于Hyperledger Fabric平台实现基于侧链的水产品跨链交易原型系统。实验结果表明，该模型能有效避免主链接入跨链的私钥暴露，降低隐私泄露风险。在交易量较大的情况下，平均交易成功率稳定高于99%，平均交易延迟时间稳定低于0.3s。并且，通过使用侧链能有效分担主链查询压力，使用超过10000条数据的并行查询测试表明，查询效率提升约35%。

Abstract:

The cross-chain technology addresses the issue of information silos between the blockchains of different enterprises in the aquatic product supply chain. However, there is a risk of privacy leakage during cross-chain transactions. To enhance the security and privacy of cross-chain transactions for aquatic products, based on the business processes of aquatic product transactions and existing cross-chain technologies, a cross-chain transaction model for aquatic products was proposed by using sidechains. The model designed an interoperation process for assets between the main chain and sidechains, and a two-way anchoring of assets between the main chain and sidechains was implemented through smart contracts. Based on the characteristics of aquatic product cross-chain transactions, the model designed the data structure and transaction process for cross-chain data. A three-phase commit protocol was used to ensure data consistency in cross-chain transactions, improve the transaction success rate, and refine the handling process for transaction failures. Additionally, to address the potential double-spending issue introduced by sidechains, a monitoring method was adopted for control. Finally, a prototype system for cross-chain transactions of aquatic products using sidechains was implemented on the Hyperledger Fabric platform. The system architecture was structured with dedicated functional modules to support secure asset transfer, cross-chain data validation, and coordinated transaction management across participating enterprises, ensuring robustness and operational efficiency. Experimental results showed that this model effectively prevented the exposure of private keys when connecting the main chain to cross-chain operations, reducing the risk of privacy leakage. Under high transaction volumes, the average transaction success rate remained consistently above 99%, and the average transaction delay remained below 0.3s. Furthermore, by using sidechains to offload the query pressure on the main chain, parallel query tests with over 10 000 data points demonstrated a query efficiency improvement of approximately 35%.