Product counterfeiting is a growing problem worldwide, threatening the health of consumers and

reducing company profits. By detecting and intercepting counterfeits before they reach the customer,

the problem can be mitigated. In this paper, an approach to detect counterfeit items based on their

claimed history is presented. The necessary data is provided by tracking infrastructures that enable

the recording and retrieval of movements of individual items in the supply chain based on unique

identifiers assigned to products. If the movement history of an item deviates from the movements of

genuine items that have been learned before, a warning about a potential counterfeit is issued.

Counterfeiter activities that are possible in a tracking enabled environment are modelled and the

capability of the proposed approach to detect these strategies is assessed.