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Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions.

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Owing to the advancement of security technologies, several encryption methods have been proposed. Despite such efforts, forging artifices is financially and somatically becoming a constraint for individuals and society (e.g.,… Click to show full abstract

Owing to the advancement of security technologies, several encryption methods have been proposed. Despite such efforts, forging artifices is financially and somatically becoming a constraint for individuals and society (e.g., imprinting replicas of luxury goods or directly life-connected medicines). Physically unclonable functions (PUFs) are one of the promising solutions to address these personal and social issues. The unreplicability of PUFs is a crucial factor for high security levels. Here, this study proposes a visually hidden and self-assembled porous polymer (VSPP) as a tag for optical PUF systems. The VSPP has virtues in terms of wavelength dependency, lens-free compact PUF system, and simple/affordable fabrication processes (i.e., spin coating and annealing). The VSPP consists of an external saturated surface, which covers the inner structures, and an internally abundant porous layer, which triggers stochastic multiple Mie scattering with wavelength dependency. We theoretically and experimentally validate the unobservability of the VSPP and the uniqueness of optical responses by image sensors. Finally, we establish a wavelength-dependent PUF system by using the following three components: solid-state light sources, a VSPP tag, and an image sensor. The captured raw images by the sensor serve as "seed" for unique bit sequences. The robustness of our system is successfully confirmed in terms of bit uniformity (∼0.5), intra/interdevice Hamming distances (∼0.04/∼0.5), and randomness (using NIST test).

Keywords: physically unclonable; hidden self; self assembled; assembled porous; unclonable functions; visually hidden

Journal Title: ACS applied materials & interfaces
Year Published: 2023

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