To Implement and Identify Counterfeiting Product in Supply Chain Based on Blockchain

Counterfeit products pose a significant challenge to supply chain management, threatening consumer safety and brand reputation. Despite advances in blocking and QR code technology for product authentication, the detection of newly introduced counterfeit products remains a significant research gap. This paper proposes a new approach for counterfeit product detection based on blockchain technology. By combining dynamic QR code generation with blockchain-based recognition, the system ensures that each product has a unique digital identity, reducing the risk of counterfeiting. Machine learning algorithms are used for anomaly detection, allowing the system to adaptively identify artificial patterns and reduce reliance on static historical data. In addition, risk mitigation strategies such as multi-factor recognition were developed to reduce false positives when fraud is detected. The effectiveness of the proposed solution is evaluated through rigorous testing with real supply chain data and simulated mock scenarios. The results demonstrate the security of product identification and confidence in product authenticity in the supply chain sector.