An Ultrahigh-Throughput and FPGA-Compatible TRNG Based on Dynamic Hybrid Metastability and Jitter Entropy Cells

Abstract

The entropy source is the most critical component of a true random number generator (TRNG), which determines the quality of the random numbers. Current TRNGs mainly utilize a specific source of physical randomness as the entropy source, but it is difficult for this method to achieve a balance between low resource overhead and high throughput. This paper explores the self-feedback multiplexer (SFMUX) structure to obtain a novel dynamic hybrid entropy source for TRNGs. Unlike other MUX-based entropy source circuits, our SFMUX cross-connects the outputs of four independent high-frequency ring oscillators (ROs) as the input signals of four MUXs, and the output of each MUX is self-fed back to serve as a selection signal. Thus, the SFMUX can not only output jitter, but also update the selection signal rapidly and randomly, which increases the probability that the SFMUX outputs unstable signals. When using a D-flip-flop (DFF) to sample this signal, the DFF may become metastable. Modeling the entropy source shows that connecting 1-stage ROs and 2-stage ROs to each SFMUX can achieve higher minimum entropy than using ROs with other numbers of stages. The proposed TRNG design is implemented on Xilinx Virtex-6, Artix-7 and Kintex-7 FPGAs. The experimental results demonstrate that our TRNG achieves a maximum throughput of 550 Mbps while using only 6 slices, and it passes the NIST, AIS-31 and Dieharder tests without postprocessing.