The 3-D NAND flash memory has become anintegral part of the cyber-physical systems to cope with thehuge data explosion in this era of Internet of Things (IoT).Moreover, hardware security primitives such as physicalunclonable function (PUF) have become indispensable inthe functional circuits of these cyber-physical systems forprotection against security vulnerabilities and adversaryattacks. Therefore, in this paper, for the first time, we propose a PUF exploiting the intrinsic variability in the stringcurrent of the ubiquitous 3-D NAND flash memory owing to theprocess variations and the inherent material imperfectionssuch as grain boundaries and the associated traps. With theaid of the Monte Carlo simulations utilizing a calibrated compact model for 3-D nand flash memory, we demonstrate thatthe proposed PUF exhibits excellent performance metricssuch as uniformity (UF) (50%), diffuseness (DF) (50%), anduniqueness (UQ) (50.08%) and is resilient to the machinelearning attacks. The ultradense 3-D NAND flash memoryarray also enables a significantly large set of challengeresponse pairs (CRPs) for a strong PUF action.
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