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Traceability anti-counterfeiting system based on the ownership of edge computing on the blockchain

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Abstract

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.

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Correspondence to Zehuan Qiu.

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Qiu, Z., Zhu, Y. Traceability anti-counterfeiting system based on the ownership of edge computing on the blockchain. J Ambient Intell Human Comput 14, 257–270 (2023). https://doi.org/10.1007/s12652-021-03290-x

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