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.
It is the goal of this workshop to bring together researchers from the fields of recommender systems, pervasive computing, mobile computing, urban sensing, social networking, context-aware systems and...