High throughput true random number generator based on dynamically superimposed hybrid entropy sources

Abstract

True random number generator is a crucial hardware system component that is widely used in the fields of cryptographic communication, key generation, statistical simulation, and secure authentication. However, the related TRNG suffers from low throughput and high resource overhead due to relying on a single entropy source. To address this issue, a TRNG circuit implementation scheme based on a MUX-XOR gate cell (MX-cell) is proposed, which uses the switching characteristics of the MUX and the XOR gate to generate metastability and jitter to develop a hybrid entropy source. It further enables the dynamic superposition of entropy sources under prescribed conditions, which improves the TRNG throughput while reducing the resource overhead. The proposed TRNG is implemented on Xilinx Artix-7 and Kintex-7 FPGAs with automatic placement and routing, passing NIST, AIS-31, TESTU01 statistical test suites and a series of other performance tests without post-processing. The experimental results reveal that the suggested design consumes only 19 LUTs, 8 DFFs, and 4 MUXs to provide random numbers with up to 380 Mbps throughput, which demonstrates highly efficient resource utilization compared to advanced published TRNGs.