A true random bit generator based on a memristive chaotic circuit: Analysis, design and FPGA implementation

Karakaya, Barış; Gülten, Arif; Frasca, Mattia

doi:10.1016/j.chaos.2018.12.021

Cited by 115 publications

(38 citation statements)

References 17 publications

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“…A serious problem of TRNG structures is that they require post-processing [8], [14], [25]- [28]. The aim of the postprocessing is to eliminate the statistical dependence between the obtained data.…”

Section: Performance Comparisons and Discussionmentioning

confidence: 99%

“…However, this additional workload eliminates the advantageous aspect of the discrete time chaotic systems. As an alternative to these RNG based on discrete time chaotic systems, various designs based on continuous time chaotic systems are proposed [9], [10], [16], [22], [28]. However, these systems have serious problems.…”

Section: Performance Comparisons and Discussionmentioning

confidence: 99%

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A Novel Random Number Generator Based on Fractional Order Chaotic Chua System

Özkaynak¹

2020

ELEKTRON ELEKTROTECH

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One of the practical applications of chaotic systems is the design of a random number generator. In the literature, generally random number generators are designed using discrete time chaotic systems. The reason for the use of the discrete time chaotic systems in the design architecture is that the latter have a simpler structure than the continuous time chaotic systems. In order to observe chaos in continuous time systems, the system must have at least three degrees. It is shown that for fractional order chaotic systems chaos can be observed even in a lower system degree. The aim of this study is to develop a random number generator using a fractional order chaotic Chua system. The proposed generator is analysed using various randomness tests. The analysis results show that the proposed generator passes the random requirements successfully. On the one hand, this study is important because it demonstrates the practical application of fractional order chaotic systems. On the other hand, it provides an alternative to designs based on discrete time chaotic systems.

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Section: Performance Comparisons and Discussionmentioning

confidence: 99%

Section: Performance Comparisons and Discussionmentioning

confidence: 99%

A Novel Random Number Generator Based on Fractional Order Chaotic Chua System

Özkaynak¹

2020

ELEKTRON ELEKTROTECH

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“…As shown in Table 8, the evaluation index indicates that the data generated by the PRNG based on the logistic chaotic system is the requirement to meet the randomness. The detection results show that the frequency is 0.556298, which indicates that the ratio of 0 and 1 in the generated sequence is relatively average [24], compared with 0.635558 in [7], 0.1329 in [16] and 0.629806 in [22], which is better than them respectively.…”

Section: Nist Analysismentioning

confidence: 99%

“…On the one hand, the extreme sensitivity of chaotic systems to initial conditions makes chaotic systems very attractive for cryptographic applications, especially for pseudo-random number generators (PRNGs) [7,[9][10][11][12][13][14][15][16][17][18][19][20][21]. Several chaotic systems have been successfully used [8] and play an important role in many applications such as numerical simulations, the game industry, communication and stochastic computation [22].…”

Section: Introductionmentioning

confidence: 99%

Pseudo-Random Number Generator Based on Logistic Chaotic System

Wang

Cheng

2019

Entropy

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In recent years, a chaotic system is considered as an important pseudo-random source to pseudo-random number generators (PRNGs). This paper proposes a PRNG based on a modified logistic chaotic system. This chaotic system with fixed system parameters is convergent and its chaotic behavior is analyzed and proved. In order to improve the complexity and randomness of modified PRNGs, the chaotic system parameter denoted by floating point numbers generated by the chaotic system is confused and rearranged to increase its key space and reduce the possibility of an exhaustive attack. It is hard to speculate on the pseudo-random number by chaotic behavior because there is no statistical characteristics and infer the pseudo-random number generated by chaotic behavior. The system parameters of the next chaotic system are related to the chaotic values generated by the previous ones, which makes the PRNG generate enough results. By confusing and rearranging the output sequence, the system parameters of the previous time cannot be gotten from the next time which ensures the security. The analysis shows that the pseudo-random sequence generated by this method has perfect randomness, cryptographic properties and can pass the statistical tests.

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“…[5] Since chaotic regimes exhibit very complicated dynamic features, they have found applications in secure data processing for confusion and diffusion operations as well as true random numbers generation for security keys. [6][7][8] These devices have been extensively developed and widely used in kHz, MHz and GHz frequency domains as a result of comparatively easy design and analysis based on the concept of linear (resistors, inductors, capacitors) and nonlinear (e.g., diodes, triodes, operational amplifiers) lumped elements. However, modern telecommunication and information technologies require much higher operational frequencies where lumped elements cannot be obtained by straightforward scaling down the size, since material dispersion significantly alters properties of metals and dielectrics and the critical latency in interconnections appears.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Nanophotonic Circuitry: Tristable and Astable Multivibrators and Chaos Generator

Gao

Ginzburg

et al. 2020

Laser & Photonics Reviews

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The concept of lumped optical nanoelements (or metactronics), wherein nanometer‐scale structures act as nanoinductors, nanocapacitors, and nanoresistors, has attracted a great deal of attention as a simple toolbox for engineering different nanophotonic devices in analogy with microelectronics. While recent studies of the topic have been predominantly focused on linear functionalities, nonlinear dynamics in microelectronic devices plays a crucial role and provides a majority of functions, employed in modern applications. Here, the metactronics paradigm is extended and nonlinear dynamical modalities are added to those nanophotonic devices that have never been associated with optical nanoantennas. Specifically, it is shown that nonlinear dimer nanoantennae can operate in the regimes of tristable and astable multivibrators as well as chaos generators. The physical mechanism behind these modalities relies on the Kerr‐type nonlinearity of nanoparticles in the dimer enhanced by a dipolar localized surface plasmon resonance. This allows one to provide a positive nonlinear feedback at moderate optical intensities, leading to the desired dynamical behavior via tuning the driving field parameters. The findings shed light on a novel class of nonlinear nanophotonic devices with a tunable nonlinear dynamical response.

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A true random bit generator based on a memristive chaotic circuit: Analysis, design and FPGA implementation

Cited by 115 publications

References 17 publications

A Novel Random Number Generator Based on Fractional Order Chaotic Chua System

A Novel Random Number Generator Based on Fractional Order Chaotic Chua System

Pseudo-Random Number Generator Based on Logistic Chaotic System

Nonlinear Nanophotonic Circuitry: Tristable and Astable Multivibrators and Chaos Generator

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