A novel control method to counteract the dynamical degradation of a digital chaotic sequence

Chen, Chen; Sun, Kehui; Peng, Yuexi; Alamodi, Abdulaziz O. A.

doi:10.1140/epjp/i2019-12374-y

Cited by 41 publications

(23 citation statements)

References 36 publications

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“…Auto correlation (AC) is also a significant factor used to evaluate the dynamical characteristics of a chaotic system. The correlation is defined as follow [33]:…”

Section: E Auto Correlationmentioning

confidence: 99%

Image Encryption Based on Improved Lorenz System

et al. 2020

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This paper proposes a new method to strengthen the nonlinear kinetic complexity and ergodicity of Lorenz system. Through the analysis of auto-correlation, frequency distribution, approximate entropy and information entropy, the improved Lorenz system has better dynamical properties than Lorenz system. According to NIST-800-22 test results, the chaotic sequences generated from proposed system have passed all random tests, which denotes that the improved Lorenz system is applicable to chaotic encryption. Once the plaintext image is color, the size of scramble image is three times as big as plaintext image, so that a lot more pixel information participant in permutation and diffusion to get better encryption results. Simulation results show that the image encryption scheme provides good security and high capacity to resist common attacks.

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“…Auto correlation (AC) is also a significant factor used to evaluate the dynamical characteristics of a chaotic system. The correlation is defined as follow [33]:…”

Section: E Auto Correlationmentioning

confidence: 99%

Image Encryption Based on Improved Lorenz System

et al. 2020

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“…In this test, the bit change rate can be used to measure its sensitivity to the key [97]- [99], that is, when the key changes slightly, the number of bits in the sequence generated by the PRNG is different. The ideal bit change rate is 50% and the closer the simulation result is to 50%, the better the sensitivity of PRNG to initial value is.…”

Section: Key Sensitivitymentioning

confidence: 99%

Design and FPGA Implementation of a Pseudorandom Number Generator Based on a Four-Wing Memristive Hyperchaotic System and Bernoulli Map

Wan

Jin

et al. 2019

IEEE Access

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Random numbers are widely used in the fields of computer, digital signature, secure communication and information security. Especially in recent years, with the large-scale application of smart card and the demand of information security, the demand for high-quality random number generator is increasingly urgent. With the development of the theory of non-linear systems, the design of pseudorandom number generator (PRNG) for chaotic behavior of non-linear systems provides a new theoretical basis and implementation method. This paper presents a PRNG based on a no-equilibrium four-wing memristive hyperchaotic system (FWMHS) and its implementation on Field Programmable Gate Array (FPGA) board. In order to increase the output throughput and the statistical quality of the generated bit sequences, we propose the PRNG design which uses a dual entropy sources architecture with FWMHS and Bernoulli map. Simulation and experimental results verifying the feasibility of the FWMHS are also given. Then, the proposed PRNG system is modeled and simulated on the Vivado 2018.3 platform, and implemented on the Xilinx ZYNQ-XC7Z020 FPGA evaluation board. The maximum operating frequency has been achieved as 135.04 MHz with a speed of 62.5 Mbit/s. Finally, we have experimentally verified that the binary data obtained by this dual entropy sources architecture pass the tests of NIST 800.22, ENT and AIS.31 statistical test suites with XOR function post-processing for a high throughput speed. The security analysis is carried out by means of dynamical degradation, key space, key sensitivity, correlation and information entropy. Statistical tests and security analysis show that it has good pseudorandom characteristics and can be used in chaos-based cryptographic applications at hardware or software implementation. INDEX TERMS Pseudorandom number generator (PRNG), FPGA, four-wing memristive hyperchaotic system (FWMHS), Bernoulli map, security analysis.

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“…More importantly, the final effect of this scheme depends on the switching rule and the switching system to a great extent, such that it is difficult to guarantee universality. The fourth is the perturbation mechanism [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. Liu and Lin [ 23 ] created perturbation chaotic systems to perturb state variables and system parameters with a logistic map.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Control of Digital Baker Map with Application to Pseudo-Random Number Generator

Shi

Deng

2021

Entropy

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Dynamical degradation occurs when chaotic systems are implemented on digital devices, which seriously threatens the security of chaos-based cryptosystems. The existing solutions mainly focus on the compensation of dynamical properties rather than on the elimination of the inherent biases of chaotic systems. In this paper, a unidirectional hybrid control method is proposed to improve the dynamical properties and to eliminate the biases of digital chaotic maps. A continuous chaotic system is introduced to provide external feedback control of the given digital chaotic map. Three different control modes are investigated, and the influence of control parameter on the properties of the controlled system is discussed. The experimental results show that the proposed method can not only improve the dynamical degradation of the digital chaotic map but also make the controlled digital system produce outputs with desirable performances. Finally, a pseudorandom number generator (PRNG) is proposed. Statistical analysis shows that the PRNG has good randomness and almost ideal entropy values.

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A novel control method to counteract the dynamical degradation of a digital chaotic sequence

Cited by 41 publications

References 36 publications

Image Encryption Based on Improved Lorenz System

Image Encryption Based on Improved Lorenz System

Design and FPGA Implementation of a Pseudorandom Number Generator Based on a Four-Wing Memristive Hyperchaotic System and Bernoulli Map

Hybrid Control of Digital Baker Map with Application to Pseudo-Random Number Generator

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