In the context of globalized supply chains, counterfeiting of manufactured goods is a growing problem. The financial, legal, and reputational costs that counterfeit goods impose on legitimate enterprises have spurred investigation into efficient and robust anti-counterfeiting methodologies. In particular, physically unclonable functions (PUFs) have been applied effectively in several manufacturing areas, especially electronics. However, anti-counterfeiting solutions for generic manufactured goods are often expensive to make and implement, or not robust to minor damage that the goods may sustain during transport and use. In this paper, a framework for developing robust, efficient, and cost-effective optical PUFs for anti-counterfeiting of manufactured metallic goods is proposed, along with an example implementation for 4140-steel parts according to standard ASTM A29. For an input library of 50 steel micrographs, the proposed example PUF is shown to have good robustness to simulated part damage and an estimated classification error rate of less than 1%.

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