This paper explores location-based product authentication in a situation where only the past locations of products that flow in a supply chain are known. We transform location-based authentication into a pattern recognition problem and investigate different solutions based on machine-learning techniques. The proposed solutions are studied with computer simulations that model the flow of genuine and counterfeit products in a generic pharmaceutical supply chain. The results suggest that machine-learning techniques could be used to automatically identify suspicious products from the incomplete location information.
At www.llrp.org, developers and reader vendors can find LLRP libraries in C, C#, Java, Perl and a Wireshark Dissector. These libraries significantly simplify control and configuration of LLRP readers.
After a trademark dispute, the EPC Prototyping Platform is now called "Fosstrak" (previously Accada). Fosstrak stands for "free and open source software for track and trace".