A Perspective of Using Frequency-Mixing as Entropy in Random Number Generation for Portable Hardware Cybersecurity IP

Xiangye Wei, Liming Xiu, Yimao Cai

2023IEEE Transactions on Information Forensics and Security13 citationsDOI

Abstract

True random number generator (TRNG) is a crucial component in security. In typical TRNGs, entropy comes directly from device noises. In this work, an improved method of using frequency-mixing as means for enriching entropy is implemented. A group of electromagnetic waves are mixed to create an irregular waveform that is then sampled to generate a random bitstream. Some part of the bitstream is fed back to the system for influencing the future frequencies of the sourcing waves, making it a chaotic system. The circuit-level support for this TRNG is the TAF-DPS (Time-Average-Frequency Direct Period Synthesis) technology. It can be digitally implemented, making the TRNG a portable IP. The merits of this TRNG include no need of special device, no post-processing, free of bias, programmable throughput, and hard-to-recognize spectrum. Those features make the TRNG suitable for a large array of applications, particularly for security in cyberspace. This TRNG is validated by a silicon chip on a 180 nm process, also on a FPGA.

Topics & Concepts

Random number generationBitstreamComputer scienceComputer hardwareField-programmable gate arrayChipRandom seedEmbedded systemTelecommunicationsComputer securityDecoding methodsChaos-based Image/Signal EncryptionCellular Automata and ApplicationsPhysical Unclonable Functions (PUFs) and Hardware Security