Privacy-preserving clone detection for RFID-enabled supply chains

Counterfeit products cause financial losses and represent a health risk. Within RFID-enabled supply chains, where products are equipped with RFID tags, clone detection mechanisms based on tag traces can help in detecting counterfeits. These mechanisms assume that supply chain partners share (private) information to run trace analysis, and may suffer from supply chain dynamics, tag misreads, product recalls, and misdeliveries. In this work, we present a novel, effective, privacy-preserving clone detection mechanism for RFID-enabled supply chains. Our mechanism does not rely on global knowledge of supply chain structures or products flow, it is robust to recalls and misdeliveries, and considers tag misreads while evaluating the presence of counterfeits. We propose privacy-preserving implementations of our mechanism that show better performance when compared to similar implementations based on existing secure multi-party computation frameworks.