Abstract

True random number generators (TRNGs) are a fundamental resource in information security and can guarantee the absolute security of information in principle. Entropy source is the most critical part of TRNGs, which provides the unpredictability and is the root of security for TRNGs. Electrical noise, which is inevitable and unpredictable in electronic systems, is always used as entropy source for TRNGs. This review discusses the different methods to harvest electrical noise in TRNGs, including the early amplify noise based on amplifier, phase jitter based on oscillator, the effect of electrical noise on the metastable behavior and amplify noise based on chaos circuits. Each method has its own strengths in aspect of speed, cost, complexity and portability. Finally, some post-processing technologies and TRNG evaluation methods are also discussed. With this review, we hope the current spots for TRNGs using electrical noise are summarized and some possible future directions are pointed out.

Highlights

  • Random number generator is always important for information encryption and decryption, numerical simulations, lottery games and stochastic experiments [1]

  • Random number generator is divided into pseudo-random number generators (PRNGs) and true random number generators (TRNGs)

  • Electrical noise is inevitable in electronic systems

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Summary

INTRODUCTION

Random number generator is always important for information encryption and decryption, numerical simulations, lottery games and stochastic experiments [1]. For the sake of defending against such problems, TRNGs are designed by researches, which extract random numbers from physical random processes These are contrary to the pseudo-random numbers produced by computer program and can guarantee the absolute security of information in principle. Some researches focused on these problems were carried out, including Si nano-devices [15], identical inverters [16], oxide breakdown [17], [18] and random telegraph noise [19] Though these methods are valid to produce high quality true random bits, they show some great challenges when are manufactured in sub-14 nm processes. These circuits need stable supply voltage and they are sensitive to temperature and aging, which will induce device drifts.

TRNG MODEL
TRNG EVALUATIONS
CONCLUSION
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