Abstract
The pharmaceutical supply chain is increasingly tending towards multi-party collaboration and high-dimensional data flow. Currently, existing blockchain technologies lack collaborative optimization of privacy and integrity for the pharmaceutical industry. Thus, this study tries to solve these issues by designing a blockchain-based approach for preserving data privacy integrity in a pharmaceutical supply chain. First, data privacy protection algorithms along with integrity verification are designed to implement access control and prevent leakage of sensitive information. Subsequently, a bidirectional gated recurrent unit, residual network, and extreme gradient boosting are used to develop a smart contract vulnerability identification approach. Finally, a data protection model is constructed. Experiments show that the proposed data verification algorithm achieves an attribute matching success rate of 99.94%, a high-concurrency authorization error rate of 0.07%, and encryption-decryption time lower than comparison algorithms. The proposed model reaches a maximum vulnerability detection accuracy of 99.31%, an area under the curve of 0.963, a minimum response latency of 132.64 ms, and a traceability data integrity verification rate of 99.96%. The results indicate that this mechanism effectively balances data privacy protection and integrity verification requirements in the pharmaceutical supply chain and provides a new method for secure data management.
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