With the exposure of various social security issues, the issue of ownership traceability and anti-counterfeiting has received more and more attention. This paper builds a design and implementation of traceability anti-counterfeiting system based on the ownership of edge computing on the blockchain. Based on the ownership of edge computing on the blockchain, this article builds a traceability anti-counterfeiting system (BCOAS), and aims at the blockchain technology algorithm in the system process and the algorithm in the system, system traceability, system security, and scalability a traceability and anti-counterfeiting system is constructed with integrity and integrity, and the efficiency is analyzed. Taking Moutai as an example, 1800 cases of traceable source code identification are used to compare and analyze this system and JD anti-counterfeiting traceability system. This paper constructs a blockchain-based data sharing framework for ownership in a cloud environment, proposes efficient and safe ownership data sharing through blockchain, and uses a hybrid blockchain-based architecture to protect ownership. The research results show that BCOAS has successfully identified 1800 source code in 1796 cases, with an accuracy rate of 99.78%; JD traceability system has successfully identified 1800 source code in 1656 cases with an accuracy rate of 92%. In the field of edge computing, it can be said that there is a great improvement. Compared with the JD traceability system, the model constructed in this paper reduces the error rate while increasing the detection speed. Since this model does not allow infringers to invest a large amount of penetration computing power, the system can reduce the system speed with a small amount of penetration computing power. Maintain in a more reasonable range to ensure higher concealment.

随着各种社会保障问题的暴露，所有权可追溯性和防伪问题日益受到关注。本文基于区块链边缘计算的所有权，构建了可追溯防伪系统的设计与实现。基于区块链上边缘计算的所有权，构建可追溯防伪系统（BCOAS），针对系统过程中的区块链技术算法以及系统中的算法，系统可追溯性，系统安全性和可扩展性构建了具有完整性和完整性的可追溯性和防伪系统，并对其效率进行了分析。以茅台为例，1800例可追溯源代码识别案例用于比较和分析该系统与JD防伪可追溯系统。本文构建了一个用于云环境中所有权的基于区块链的数据共享框架，提出了通过区块链进行高效安全的所有权数据共享，并使用基于混合区块链的架构来保护所有权。研究结果表明，BCOAS已经成功识别出1796例案例中的1800个源代码，准确率达99.78％；JD追溯系统已成功识别出1656个案例中的1800个源代码，准确率达92％。在边缘计算领域，可以说有很大的进步。与JD可追溯系统相比，本文构建的模型在提高检测速度的同时，降低了错误率。由于此模型不允许侵权者投入大量的渗透计算能力，因此系统可以使用少量的渗透计算能力降低系统速度。保持在更合理的范围内，以确保更高的遮盖力。