Graphene-Based Physically Unclonable Functions with Dual Source of Randomness.

Abstract

There is growing interest in systems with randomized responses for generating physically unclonable functions (PUFs) in anticounterfeiting and authentication applications. Atomic-level control over its thickness and unique Raman spectrum make graphene an attractive material for PUF applications. Herein, we report graphene PUFs that emerge from two independent stochastic processes. Randomized variations in the shape and number of graphene adlayers were achieved by exploiting and improving the mechanistic understanding of the chemical vapor deposition of graphene. The randomized positioning of the graphene domains was then facilitated by dewetting the polymer film, followed by oxygen plasma etching. This approach yielded surfaces with randomly positioned and shaped graphene islands with varied numbers of layers and, therefore, Raman spectra. Raman mapping of surfaces resulted in multicolor images with a high encoding capacity. Advanced feature-matching algorithms were employed for the authentication of multicolor images. The use of two independent stochastic processes on a two-dimensional nanomaterial platform enables the creation of unique and complex surfaces that excessively challenge clonability.