DTRNG

Abstract

True Random Number Generators (TRNGs) are used in a variety of applications including cryptography, computer simulation, gambling games, machine learning and hyperdimensional computing. Dynamic Random-Access Memory (DRAM)-based TRNGs have been widely used as they are low cost and available in most modern electronic devices. However, most existing DRAM-based TRNGs produce random numbers with either hardware overhead, or low throughput. In this work, we report a novel high dense, high throughput and high entropy DRAM-based TRNG, named DTRNG, that exploits the process variations inherited by the DRAM cell's access transistor and sense amplifiers. DTRNG can be employed in commodity DRAM chips with no hardware overhead and using the standard memory controller commands. The proposed method is based on controlling the word line voltage supply part of the DRAM chip during random number mode. The novel approach provided in this work has been validated using cadence circuit tools on a constructed 8x8 DRAM chip in 65nm technology. In addition, Monte Carlo simulations are performed to verify the entropy of the generated numbers. The random sequence generated by DTRNG has passed all the NIST test without any post-processing demonstrating randomness and suitability for security scheme. DTRNG is considered a milestone towards low cost and high efficient secure hardware for AI and IoT applications.