True Random Number Generators Using Electrical Noise

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.INDEX TERMS TRNGs, electrical noise, entropy source, post-processing, evaluation methods. I. INTRODUCTIONRandom number generator is always important for information encryption and decryption, numerical simulations, lottery games and stochastic experiments [1]. Historically, random number generator is divided into pseudo-random number generators (PRNGs) and true random number generators (TRNGs).PRNGs use some initial seeds and deterministic algorithms to produce pseudo-random numbers and can result in high throughput. However, once the seeds are obtained by attacker, all security will be lost. Thus, it is dangerous that using PRNGs produce secret keys. 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.The randomness of TRNGs comes from entropy source which is the root of security for TRNGs. Electrical noise is inevitable in electronic systems. Due to the unpredictability The associate editor coordinating the review of this article and approving it for publication was Jiafeng Xie.

Towards Post-Quantum Cryptography Using Thermal Noise Theory and True Random Numbers Generation

“…x y z ν Σ = ∫∫∫ (12) We define by framing in black ( Figure 1) the considered volume elements during the temperature evaluation. They are referenced by numbering.…”

A Low Power Circuit Design for Chaos-Key Based Data Encryption

“…The explosive growth of Internet-of-Things (IoTs) devices places new challenges on random number generators including energy efficiency, hardware security, and flexibility. Nowadays, true random number generators, taking advantage of the nonlinear and dynamic characteristics of chaotic systems, are attracting substantial research interest [6]- [10]. A chaotic system, which is represented by a deterministic expression, is nonlinear and dynamic [6].…”

“…high-security applications, due to their sensitivity to initial conditions and irregular motion in the phase space. Therefore, at a certain point of observation, the chaotic system behaves as a random-like process [10]. Chaotic systems used in generating random bits are categorized into discrete and continuous systems.…”

Fast True Random Number Generator Based on Chaotic Oscillation in Self-Feedback Weakly Coupled Superlattices

“…The true random number generator (TRNG) is based on the unpredictable physical random phenomenon [6], which can generate unpredictable and unreproducible true random numbers. Representative TRNGs are mainly based on physical entropy sources such as circuit thermal noise [7], [8], oscillators [9], and chaotic circuits [10], [11]. But the rate of these random number generators is mostly at the Mbit/s level, which makes it difficult to meet the demands of modern communication systems for high-speed random numbers generation.…”