A true random number generator based on the photon arrival time registered in a coincidence window between two single-photon counting modules

Hasan, Raghad Saeed; Tawfeeq, Shelan K.; Mohammed, Nahla Qader; Khaleel, Ahmed I.

doi:10.1016/j.cjph.2017.11.008

Cited by 13 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e unpredictable and unrepeatable random number sequence which can be produced by RNG plays an important role in information encryption. Based on Shannon information theory, in order to ensure the absolute security of communication, the RNG with high speed, unpredictability, and good randomness has great research value [83][84][85][86][87][88][89].…”

Section: Introductionmentioning

confidence: 99%

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Liu

Qian

et al. 2020

Complexity

View full text Add to dashboard Cite

Novel memristive hyperchaotic system designs and their engineering applications have received considerable critical attention. In this paper, a novel multistable 5D memristive hyperchaotic system and its application are introduced. The interesting aspect of this chaotic system is that it has different types of coexisting attractors, chaos, hyperchaos, periods, and limit cycles. First, a novel 5D memristive hyperchaotic system is proposed by introducing a flux-controlled memristor with quadratic nonlinearity into an existing 4D four-wing chaotic system as a feedback term. Then, the phase portraits, Lyapunov exponential spectrum, bifurcation diagram, and spectral entropy are used to analyze the basic dynamics of the 5D memristive hyperchaotic system. For a specific set of parameters, we find an unusual metastability, which shows the transition from chaotic to periodic (period-2 and period-3) dynamics. Moreover, its circuit implementation is also proposed. By using the chaoticity of the novel hyperchaotic system, we have developed a random number generator (RNG) for practical image encryption applications. Furthermore, security analyses are carried out with the RNG and image encryption designs.

show abstract

Section: Introductionmentioning

confidence: 99%

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Liu

Qian

et al. 2020

Complexity

View full text Add to dashboard Cite

show abstract

“…The block diagram represented in Figure 1 contains operations like addition, multiplication, addition, comparison and subtraction. To simplify the work process; the circuit is intended using the 'word lengths' lessening method that has recommended in [13][14][15][16][17][18][19][20][21][22][23][24][25]. Then comparator and subtractor blocks can be merged, as shown in Figure 2.…”

Section: Figure 1 General Block Diagram Of Lcgmentioning

confidence: 99%

Co-simulation of linear congruential generator by using Xilinx system generator and MATLAB Simulink

Suneeta

2021

IJRES

View full text Add to dashboard Cite

<p>Arbitrary numerals are utilized in a wide range of uses. Genuine arbitrary numeral generators are moderate and costly for some applications while pseudo arbitrary numeral generators (RNG) do the trick for most applications. This paper fundamentally concentrates around the co-simulation of the linear congruential generator (LCG) model utilizing the Xilinx System generator and checking on Matlab Simulink. The design is obtained from the LCG calculation offered by Lehmer. Word lengths decrease strategy has been utilized to streamline the circuit. Simulation has been done effectively. The effective N bit LCG is structured and tried by utilizing demonstrating in MatLab Simulink. The Co-simulation of the model is done by utilizing the Xilinx system generator. This paper conducts an exhaustive search for the best arbitrary numeral generator in a full period linear congruential generator (LCG) with the largest prime numbers.</p>

show abstract

“…Consequently, systems relying on pseudo random number encryption are susceptible to attacks and security risks. Physical random numbers [11,12] are generated by using physical phenomena in nature as entropy sources, exhibiting a high degree of unpredictability. The main types of physical entropy sources include thermal noise [13,14], phase jitter in oscillating signals [15][16][17], chaos [18][19][20][21], and others.…”

Section: Introductionmentioning

confidence: 99%

Random Numbers Generated Based on Dual-Channel Chaotic Light

Liu,

Mu,

Wang

et al. 2024

Electronics

View full text Add to dashboard Cite

This paper presents a chaotic system based on novel semiconductor nanolasers (NLs), systematically analyzing its chaotic region and investigating the influence of key parameters on the unpredictability of chaotic output. This study found that under optical feedback conditions, NLs generate chaos across a wide range of feedback parameters, with the highly unpredictable region completely overlapping with the chaotic region. Further injection into the slave lasers enhances the chaotic output, expanding the range of unpredictability. Additionally, we analyzed the impact of internal parameter mismatch on the complexity of chaotic signals and found it to be similar to the scenario when parameters are matched. Using this chaotic system as an entropy source, we constructed a random number generator (RNG) and investigated the effects of internal parameters mismatch and differences in the injection parameters on the generator’s performance. The simulation results show that the RNG performs well under different parameter settings, and the generated random sequences pass all random number tests successfully. Therefore, this chaotic system can yield a high-complexity chaotic light source with appropriate parameter selection, and when combined with effective post-processing, it can generate high-quality random numbers. This is crucial for advancing the realization of small-sized, high-randomness RNGs.

show abstract

A true random number generator based on the photon arrival time registered in a coincidence window between two single-photon counting modules

Cited by 13 publications

References 5 publications

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Chaos-Based Application of a Novel Multistable 5D Memristive Hyperchaotic System with Coexisting Multiple Attractors

Co-simulation of linear congruential generator by using Xilinx system generator and MATLAB Simulink

Random Numbers Generated Based on Dual-Channel Chaotic Light

Contact Info

Product

Resources

About