4.6 Article

Design and implementation of blockchain-based supply chain framework with improved traceability, privacy, and ownership

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SPRINGER
DOI: 10.1007/s10586-023-04091-x

关键词

Blockchain; Supply chain; Counterfeits; Privacy; Logistics

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Blockchain technology is used to address traceability, ownership, and trust issues in the supply chain. However, privacy concerns arise when sharing information. This paper proposes a new mechanism that ensures privacy by considering traceability and ownership. The system employs a combination of symmetric and asymmetric key encryption to achieve privacy. Experimental results demonstrate that the proposed system can provide privacy without significantly impacting traceability and ownership.
Blockchain is a modern-age technology which records digital transactions in a consistent, safe, and verifiable form to solve the problems from different sectors. In the supply chain, this technology is applied to improve traceability, ownership, and trust. Moreover, it can solve the issue pertaining to counterfeits in the supply chain. However, blockchain-based supply chains have certain disadvantages, such as privacy of the information shared between the members of the supply chain. In this paper, a new mechanism has been proposed to ensure the privacy of such information by taking traceability and ownership into account. The novelty of the proposed system is its ability to achieve privacy with the inclusion of traceability and ownership. To implement privacy, we employed a combination of symmetric and asymmetric key encryption. With the proposed system, owner of the product can trace said product and the one who owns the product can transfer the ownership. The proposed system restricts the entry of counterfeit products in the supply chain. The Hyperledger Sawtooth blockchain has been used for the experimental purpose. The subsequent analysis show that the proposed system can provide privacy without disturbing factors concerning traceability and ownership. The results show that the inclusion of privacy does not impact performance significantly.

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