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Pseudorandom number generator based on novel 2D Hénon-Sine hyperchaotic map with microcontroller implementation

Recently, chaotic maps have been considered to design pseudorandom number generator (PRNG). However, some chaotic maps present security disadvantages, such as low uniformity and low randomness properties. Nowadays, chaos-based PRNGs are used as the main source for the development of cryptographic al...

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Detalles Bibliográficos
Autores principales: Murillo-Escobar, Daniel, Murillo-Escobar, Miguel Ángel, Cruz-Hernández, César, Arellano-Delgado, Adrian, López-Gutiérrez, Rosa Martha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9702891/
https://www.ncbi.nlm.nih.gov/pubmed/36465277
http://dx.doi.org/10.1007/s11071-022-08101-2
Descripción
Sumario:Recently, chaotic maps have been considered to design pseudorandom number generator (PRNG). However, some chaotic maps present security disadvantages, such as low uniformity and low randomness properties. Nowadays, chaos-based PRNGs are used as the main source for the development of cryptographic algorithms. In this work, to overcome such weaknesses, a novel 2D hyperchaotic map is proposed based on discrete-time feedback by using Hénon map and Sine map. In addition, the dynamics of the hyperchaotic map are enhanced by using the remainder after division function (rem), where better random statistical properties are obtained. A comparison is made between the enhanced Hénon-Sine hyperchaotic map (EHSHM) and the Hénon-Sine hyperchaotic map through Lyapunov exponent analysis, attractor trajectory, histograms and sensitivity at initialization. Then, 8-bit pseudorandom number generator based on the proposed hyperchaotic map (PRNG–EHSHM) is designed and the initial seed of the PRNG is calculated by a secret key of 60 hexadecimal characters. It is implemented in both MATLAB and Arduino Mega microcontroller for experimental results. A complete security analysis is presented from a cryptographic point of view, such as key space, floating frequency, histograms and entropy of the information. Moreover, the randomness is verified with the tests of the National Institute of Standards and Technology (NIST 800-22). Based on the security results obtained, the proposed PRNG–EHSHM can be implemented in embedded cryptographic applications based on chaos.