Counterfeiting is a worldwide issue affecting many industrial sectors, ranging from specialized technologies to retail market, such as fashion brands, pharmaceutical products, and consumer electronics. Counterfeiting is not only a huge economic burden (>$ 1 trillion losses/year), but it also represents a serious risk to human health, for example, due to the exponential increase of fake drugs and food products invading the market. Considering such a global problem, numerous anticounterfeit technologies have been recently proposed, mostly based on tags. The most advanced category, based on encryption and cryptography, is represented by physically unclonable functions (PUFs). A PUF tag is based on a unique physical object generated through chemical methods with virtually endless possible combinations, providing remarkable encoding capability. However, most methods adopted nowadays are based on expensive and complex technologies, relying on instrumental readouts, which make them not effective in real-world applications. To achieve a simple yet cryptography-based anticounterfeit method, herein we exploit a combination of nanotechnology, chemistry, and artificial intelligence (AI). Notably, we developed platinum nanocatalyst-enabled visual tags, exhibiting the properties of PUFs (encoding capability >10300) along with fast (1 min) ON/OFF readout and full reversibility, enabling multiple onsite authentication cycles. The development of an accurate AI-aided algorithm powers the system, allowing for smartphone-based PUF authentications.
Keywords: AI-aided authentication; anticounterfeiting; colorimetric; physically unclonable functions; platinum nanocatalysts.