A Survey on Diamond Security System Using Machine Learning and Blockchain

Abstract

The pervasive challenges of counterfeit in the diamond industry, cybersecurity vulnerabilities, and the looming threat of large-scale heists, akin to the infamous Antwerp money heist of 2003, underscore the critical need for innovative security solutions. This initiative addresses these pressing concerns through the fusion of machine learning algorithms and blockchain technology. Our methodology entails a comprehensive dataset comprising 32 parameters for advanced detection and 5 dominant parameters for basic detection, catering to both expert and novice users. Leveraging machine learning techniques including random forest and ensemble learning, our system meticulously analyzes these parameters to discern between natural and artificial diamonds with heightened accuracy. The accuracy of our models varies, with the highest achieving an impressive 98%, ensuring robust authentication and fraud prevention mechanisms. Furthermore, the verified data of natural diamonds is securely stored on a blockchain ledger, fortifying ownership records against tampering and ensuring transparency. This integrated approach not only safeguards the integrity of the diamond industry but also fosters trust and transparency among stakeholders. By providing a paradigm shift in security solutions, our system sets a new standard for authentication and fraud prevention in the diamond market, mitigating risks and empowering stakeholders with reliable, data-driven tools for decision-making.