A Blockchain-based Traceability Method for Automotive Parts in Supply Chain

This paper presents a blockchain-based method for traceability of supply chain parts to address the complexity and security challenges within the automotive industry's supply chain. Leveraging blockchain's decentralized and tamper-resistant properties, combined with a dynamic broadcast mechanism and binary Merkle tree structure, this approach effectively improves data transparency and privacy protection. Test results indicate that the method achieves a 97% accuracy rate in tamper detection and enhances traceability speed by 30% over traditional methods, underscoring notable advantages in real-time performance and security. This approach offers a novel solution for enhancing the intelligence and security of supply chain management, with promising applications for the future.