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.

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Disturbance rejection performance for rolling hydraulic position control system has always been a knotty issue. To guarantee the transient performance and improve disturbance rejection performance of the rolling hydraulic position control system, a compound controller, composed of a feedforward controller part based on proportional integral laws and a compensation part based on disturbance observer, is designed and investigated. In this article, a detailed analysis and design principles of the composite controller are provided. Additionally, stability analysis of the controller is proved using Lyapunov function adapted to the system. Finally, a rigorous analysis of the disturbance rejection performance is given with consideration of both instantaneous disturbances and low-frequency disturbances. For single pulse disturbance, the maximum error is reduced from 3.5% to 0.6%. Furthermore, for more complicated disturbance, sinusoidal disturbance is lower than 50 Hz, disturbance rejection performance decreases with increasing frequency and maximum error is reduced from 5.4% to 1.6%. The test results demonstrate that for single pulse disturbance, the maximum error is reduced from 4.12% to 0.64%. Furthermore, for more complicated disturbance, sinusoidal disturbance is lower than 50 Hz, disturbance rejection performance decreases with increasing frequency and maximum error is reduced from 2.71% to 0.70%. Both simulation and experiment results demonstrate that the proposed method possesses a better disturbance rejection performance than the proportional integral method.

In this paper, a deep learning (DL)-based predictive analysis is proposed to analyze the security of a non-deterministic random number generator (NRNG) using white chaos. In particular, the temporal pattern attention (TPA)-based DL model is employed to learn and analyze the data from both stages of the NRNG: the output data of a chaotic external-cavity semiconductor laser (ECL) and the final output data of the NRNG. For the ECL stage, the results show that the model successfully detects inherent correlations caused by the time-delay signature. After optical heterodyning of two chaotic ECLs and minimal post-processing are introduced, the model detects no patterns among corresponding data. It demonstrates that the NRNG has the strong resistance against the predictive model. Prior to these works, the powerful predictive capability of the model is investigated and demonstrated by applying it to a random number generator (RNG) using linear congruential algorithm. Our research shows that the DL-based predictive model is expected to provide an efficient supplement for evaluating the security and quality of RNGs.

Boolean chaos is widely used in physical systems for its digital-like behavior and complex dynamics. However, electronic logic devices limit the bandwidth of Boolean chaos and its development. Based on an autonomous optical Boolean network, a method of generating optical Boolean chaos with 14 GHz bandwidth is proposed, exploring the physical mechanism of the chaos generated by the system and analyzing the influences of external parameters on the dynamic characteristics of the system. The output status is mainly affected by the detection optical power, carrier recovery time of the semiconductor optical amplifier, and difference between the two self-feedback time delays.