Securing Drug Traceability: Blockchain-Enhanced Privacy Protection and Anti-Counterfeit Measures in Pharmaceutical Supply Chains

Background

The pharmaceutical sector is under severe threat in ensuring the genuineness of drugs and securing sensitive information throughout the supply chain. Conventional security measures tend to be ineffective in addressing these issues comprehensively, resulting in weaknesses like counterfeit medicines and illegitimate access to data.

Objective

This research suggests an integrated, state-of-the-art security system to provide improved data protection, encryption effectiveness, and supply chain integrity in the pharmaceutical industry.

Methods

The suggested framework utilizes Attribute-Based Encryption (ABE) in conjunction with QR code technology for secure, fine-grained data encryption. For the optimization of encryption key selection, a hybrid optimization method combining Red Panda Optimization (RPO) Algorithm and Group Teaching Optimization Algorithm (GTOA) is proposed. Additionally, Multi-Party Computation (MPC) protocols and Shamir’s Secret Sharing scheme are used to guarantee that only legitimate parties can reconstruct and view important data, maintaining confidentiality and integrity.

Results

Performance testing shows that the framework proposed performs better than traditional cryptos. Encryption time registered was at 0.21234 seconds, which was quicker than RSA (0.308372) and 3DES (0.36462). Decryption took 0.22112 seconds, which was faster than RSA’s 0.312773. Total turnaround time was cut to 0.431231 seconds, which was far superior to Blowfish at 0.52356 seconds. The system also attained a restoration efficiency level of 0.987453, ahead of RSA at 0.92133 and Blowfish at 0.94109.

Conclusion

The security model offers a secure and feasible solution for end-to-end data protection and prevention of tampering and unauthorized access in the pharma supply chain.