A no-equilibrium memristive system with four-wing hyperchaotic attractor

Rajagopal, Karthikeyan; Bayani, Atiyeh; Khalaf, Abdul Jalil M.; Namazi, Hamidreza; Jafari, Sajad; Pham, Viet–Thanh

doi:10.1016/j.aeue.2018.08.022

Cited by 51 publications

(14 citation statements)

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“…The four-wing hyperchaotic system based on a memristor is a research hotspot at present. Many different four-wing hyperchaotic systems based on a memristor have been introduced successively [81], [82], [88]. Recently, a no-equilibrium FWMHS was proposed in [88] by considering a control parameter.…”

Section: The Mathematical Models Of Fwmhs and Bernoulli Map A A mentioning

confidence: 99%

“…Many different four-wing hyperchaotic systems based on a memristor have been introduced successively [81], [82], [88]. Recently, a no-equilibrium FWMHS was proposed in [88] by considering a control parameter. The FWMHS shows both the no equilibrium and line equilibrium conditions for different values of the control parameter.…”

Section: The Mathematical Models Of Fwmhs and Bernoulli Map A A mentioning

confidence: 99%

“…and where x, y, z, w are state variables and W (w) is the memductance, that represents the non-linearity of the flux-controlled memristor with parameters m and n. Q is the control parameter, when Q = 0, the FWMHS exhibits hyperchaotic attractors without equilibrium points; When Q = 0, the system has a line equilibrium in (0, 0, 0, w) and this line equilibrium is consisting of infinite unstable [88]. To obtain a hyperchaotic With respect to performed analysis, the Lyapunov exponents have been calculated as LE1 = 0.1032, LE2 = 0.0149, LE3 = 0 and LE4 = −1.996 when Q = 0.01.…”

Section: The Mathematical Models Of Fwmhs and Bernoulli Map A A mentioning

confidence: 99%

“…Multistability refers to coexisting of multiple attractors depending on different initial conditions, which is the inherent characteristic of nonlinear systems and shows the rich multiple steady state of the nonlinear dynamic system. In order to study the multistability of the FWMHS, we change the initial conditions and control parameter Q, and keep the system other parameters unchanged to observe the attractor phenomenon, and find that the system has hidden and multistable attractors [88]. When −0.05055 < Q < 0.0513, we can see coexisting attractor with a limit cycle and coexisting attractors of Q = 0.0505 as shown in Fig.…”

Section: The Mathematical Models Of Fwmhs and Bernoulli Map A A mentioning

confidence: 99%

“…In the present paper, based on a no-equilibrium four-wing memristive hyperchaotic system (FWMHS) introduced in [88], a PRNG used in FPGA-based design is proposed. Most importantly, the novel PRNG uses a dual entropy sources architecture with FWMHS and Bernoulli map to increase the output throughput and the statistical quality of the generated bit sequences.…”

Section: Introductionmentioning

confidence: 99%

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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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