Journal
CHAOS SOLITONS & FRACTALS
Volume 161, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2022.112296
Keywords
PRNG; Deepzoom; Chaoscryptography
Categories
Funding
- Sao Paulo Research Foundation FAPESP [22/01935-2, 21/07377-9]
- FAPESP [2020/03514-9, 21/08325-2, 307897/2018-4]
- CNPq [18/22214-6]
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [22/01935-2, 21/07377-9, 21/08325-2] Funding Source: FAPESP
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This paper proposes the deep-zoom analysis of the composition of the logistic map and the tent map, and finds that the pseudo-random qualities of the composition map improve as the parameter k increases. The application of deep-zoom to the composition of chaotic maps is suitable for better randomization for PRNG purposes as well as for cryptographic systems.
We propose the deep-zoom analysis of the composition of the logistic map and the tent map, which are well-known discrete one-dimensional chaotic maps. The deep-zoom technique transforms each point of a given cha-otic orbit by removing the first k-digits after decimal separator. We found that the pseudo-random qualities of the composition map as a pseudo-random number generator (PRNG) improve as the k parameter increases. This was evidenced by the fact that it successfully passed the randomness tests and even outperformed the k-logistic map and the k-tent map PRNG. These dynamic properties show that the application of deep-zoom to the composition of chaotic maps, at least to these two well-known maps, is suitable for better randomization for PRNG purposes as well as for cryptographic systems.(c) 2022 Published by Elsevier Ltd.
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