An information theoretic approach to assist in identifying counterfeit consumer goods

In an increasingly connected world where products are just a click away, there is a growing need for systems that seek to equip consumers with the necessary tools to identify misrepresented products. Sub-standard ingredients used in the production of sanitary towels can pose a serious health risk to the consumer. Informal retailers or Spaza-shops have been accused of selling counterfeit food products to unsuspecting consumers. In this paper, we propose a system that can be used by consumers to scan a quick response (QR) code printed on the product. Built into an android application, is a system that applies the RSA public key encryption algorithm to secure the data prior to encoding into the QR code. The proposed system is also responsible for updating location data of previous scans on a dedicated cloud database. Upon completion of a field test, having collected months of consumer data, counterfeit prediction can be improved. In addition, a timely warning can be sent to a customer and relevant authorities if a unique product batch number is scanned outside of an expected area.