Simulation of a randomly percolated CNT network for an improved analog physical unclonable function

Abstract

Abstract As the Internet of Things (IoT) continues to expand, research on an alternative encryption technology, the physically unclonable function (PUF), is increasing. Carbon nanotube (CNT) network-based PUFs have the great advantage of having a very simple process and being compatible with CMOSs, but since the randomness varies greatly depending on the process conditions, it is necessary to investigate various process parameters to have excellent PUF performance. For this purpose, we implemented a random CNT network using simulation and constructed an analog PUF with resistance values as data through numerous iterations. At this time, new evaluation methods were presented to compare the performance of the analog PUF, and the optimal point of PUF performance was identified by comparing the performance according to two process parameters, CNT density and metallic CNT ratio. Our study can serve as a guide for producing an optimized CNT PUF in the future after the CNT solution and processing method are clarified. This will be a PUF with a small footprint area, high CMOS compatibility, and superior security compared to a digital PUF.