Anti-Fraud Detection System Based on Microwave Spectral Signature of Chipless RFID and Machine Learning

In conjunction with the rapid evolution of global web markets and online transactions, there is a strong increase in frauds that involve luxury goods and foods. In such a scenario, the development of new methodologies to protect the brand’s originality is mandatory. Different research groups tried to propose a wide range of anti-fraud systems aimed at protecting luxury goods and foods. They are based on radio frequency identification (RFID) technology, advanced deep and machine learning methods, and blockchain. This article presents a system that permits the easy and unique identification and tracking of luxury goods starting from the production phase using chipless RFID tags. The method uses metallic tags that are difficult to imitate and that can be hidden in the good. To simplify the tag identification, machine learning techniques are implemented in the reader section. Obtained preliminary results, based on an experimental system prototype, are quite promising and have shown a protection accuracy enhancement compared with existing methodologies.