Abstract

Physical unclonable function (PUF) has been an effective solution for hardware security with the popularity of the internet of things (IoT). Due to low power consumption and high area efficiency, an emerging nonvolatile memory, resistive random access memory (RRAM) based PUF designs have attracted many attentions. Due to the bottleneck in the existing RRAM PUFs that it can not be fully compatible with the memory architecture, a dynamically configurable PUF based on the mainstream RRAM crossbar is proposed in this paper. Utilizing the device-to-device variation of the RRAM resistance, abundant challenge-response pairs (CRPs) are generated with a flexible configuration of an RRAM crossbar. Furthermore, different from the existing RRAM-based PUF designs, the proposed RRAM PUF can be dynamically configured between a memory cell and a PUF cell, without requiring additional sense circuits, leading to a minimal design overhead. The simulation results show that the proposed PUF exhibits good performance with a high uniqueness and reliability. Moreover, it achieves a great resistance against machine learning (ML) attack.

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