基于区块链的远洋捕捞产品新鲜度评价与可信追溯模型研究

Freshness Evaluation and Reliable Traceability Model of Pelagic Fishing Products Based on Blockchain

摘要:

针对远洋捕捞追溯流程缺少产品新鲜度定量分析，分析结果可信度差等问题，以三文鱼为例，详细分析远洋捕捞追溯流程，基于层次分析法建立了远洋捕捞产品新鲜度指标评价体系，提出新鲜度得分公式，实现了标准统一的产品新鲜度评价。结合ECDSA签名技术与智能合约实现了追溯责任的精准定位，通过引入信誉积分数据，建立了奖励、惩罚、补偿机制三位一体的企业双向信誉评价模型，保障了信誉评价主体的积极性及新鲜度得分数据的真实性，实现了产品新鲜度的可信追溯。安全性分析表明信誉积分的攻击难度等价于ECDSA私钥的破解难度，证明了信誉评价模型可信、安全及不可篡改的特性。性能测试结果显示，追溯数据读写吞吐量保持在500笔/s与150笔/s以上，读写成功率分别为100%与98%，数据写入平均耗时为0.416 s，数据查询平均耗时为0.142 s，相比基于可靠企业信誉评估机制的区块链农产品可信追溯模型，存储与查询效率分别提升55.8%与63.4%，基本满足产品实际追溯业务需求。

Abstract:

In light of lack of quantitative analysis in the traceability process of pelagic fishing and the limited credibility of the analysis results, the traceability process of pelagic fishing was examined in detail by using salmon as an example. A freshness index evaluation system for pelagic fishing products was established based on the analytic hierarchy process. By applying this method to the evaluation of freshness, a standardized and replicable process for assessing the quality of pelagic fishing products was created, a freshness scoring formula was proposed and standardized product freshness evaluation was achieved. By incorporating ECDSA signature technology and smart contracts, accurate identification of traceability responsibility was achieved. Furthermore, by introducing credit score data, a two-way enterprise reputation evaluation model with reward, punishment, and compensation mechanisms was established to ensure both enthusiasm from credit evaluation subjects and authenticity of freshness score data. This approach enabled trusted traceability of product freshness. The security of this credit evaluation model was of paramount importance, which was addressed by ensuring that the system was as secure as the underlying ECDSA private keys, thus confirming the credibility, security, and immutability characteristics of the credit evaluation model. Performance test results indicated that read and write throughput for traceability data remained above 500TPS and 150TPS, respectively;reading success rate reached 100% while writing success rate standed at 98%. The average time for data writing was 0.416 s while data querying tooks an average time of 0.142 s. Compared with blockchain-based agricultural products trusted traceability models relying on reliable enterprise reputation evaluation mechanisms, storage efficiency was increased by 55.8%, query efficiency was improved by 63.4%, effectively meeting actual product traceability business needs.