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A team of researchers has developed a mechanism that uses machine-learning algorithms to distinguish between genuine and counterfeit versions of the same product. "The underlying principle of our system stems from the idea that microscopic characteristics in a genuine product or a class of products -- corresponding to the same larger product line -- exhibit inherent similarities that can be used to distinguish these products from their corresponding counterfeit versions," says Subramanian, a professor at NYU's Courant Institute of Mathematical Sciences. Counterfeit goods represent a massive worldwide problem with nearly every high-valued physical object or product directly affected by this issue, the researchers note. The Entrupy method, by contrast, provides a non-intrusive solution to easily distinguish authentic versions of the product produced by the original manufacturer and fake versions of the product produced by counterfeiters.