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Recent advances in predictive data analytics and ever growing digitalization and connectivity with explosive expansions in industrial and consumer Internet-of-Things (IoT) has raised significant concerns about security of people's identities and data. It has created close to ideal environment for adversaries in terms of the amount of data that could be used for modeling and also greater accessibility for side-channel analysis of security primitives and random number generators. Random number generators (RNGs) are at the core of most security applications. Therefore, a secure and trustworthy source of randomness is required to be found. Here, we present a differential circuit for harvesting one of the most stochastic phenomenon in solid-state physics, random telegraphic noise (RTN), that is designed to demonstrate significantly lower sensitivities to other sources of noises, radiation and temperature fluctuations. We use RTN in amorphous SrTiO3-based resistive memories to evaluate the proposed true random number generator (TRNG). Successful evaluation on conventional true randomness tests (NIST tests) has been shown. Robustness against using predictive machine learning and side-channel attacks have also been demonstrated in comparison with non-differential readouts methods.

The rapidly expanding hardware-intrinsic security primitives are aimed at addressing significant security challenges of a massively interconnected world in the age of information technology. The main idea of such primitives is to employ instance-specific process-induced variations in electronic hardware as a source of cryptographic data. Among the emergent technologies, memristive devices provide unique opportunities for security applications due to the underlying stochasticity in their operation. Herein, we report a prototype of a robust, dense, and reconfigurable physical unclonable function primitives based on the three-dimensional passive metal-oxide memristive crossbar circuits, by making positive use of process-induced variations in the devices' nonlinear I-Vs and their analog tuning. We first characterize security metrics for a basic building block of the security primitives based on a two layer stack with monolithically integrated 10x10 250-nm half-pitch memristive crossbar circuits. The experimental results show that the average uniformity and diffusivity, measured on a random sample of 6,000 64-bit responses, out of ~697,000 total, is close to ideal 50% with 5% standard deviation for both metrics. The uniqueness, which was evaluated on a smaller sample by readjusting conductances of crosspoint devices within the same crossbar, is also close to the ideal 50% +/- 1%, while the smallest bit error rate, i.e. reciprocal of reliability, measured over 30-day window under +/-20% power supply variations, was ~ 1.5% +/- 1%. We then utilize multiple instances of the basic block to demonstrate physically unclonable functional primitive with 10-bit hidden challenge generation that encodes more than 10^19 challenge response pairs and has comparable uniformity, diffusiveness, and bit error rate., Comment: 24 pages, 5 figures

A unique set of characteristics are packed in emerging nonvolatile reduction-oxidation (redox)-based resistive switching memories (ReRAMs) such as their underlying stochastic switching processes alongside their intrinsic highly nonlinear current-voltage characteristic, which in addition to known nano-fabrication process variation make them a promising candidate for the next generation of low-cost, low-power, tiny and secure Physically Unclonable Functions (PUFs). This paper takes advantage of this otherwise disadvantageous ReRAM feature using a combination of novel architectural and peripheral circuitry. We present a physical one-way function, nonlinear resistive Physical Unclonable Function (nrPUF), potentially applicable in variety of cyber-physical security applications given its performance characteristics. We experimentally verified performance of Valency Change Mechanism (VCM)-based ReRAM in nano-fabricated crossbar arrays across multiple dies and runs. In addition to a massive pool of Challenge-Response Pairs (CRPs), using a combination of experimental and simulation, our proposed PUF shows a reliability of 98.67%, a uniqueness of 49.85%, a diffuseness of 49.86%, a uniformity of 47.28%, and a bit-aliasing of 47.48%., Comment: 12 pages, 8 figures