Pseudo-random number generator based on mixing of three chaotic maps

François, M.; Grosges, Thomas; Barchiesi, Dominique; Erra, Robert

doi:10.1016/j.cnsns.2013.08.032

Cited by 104 publications

(69 citation statements)

References 9 publications

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“…Literature [12] designed a new pseudorandom number generator by mixing the couple map lattice technology and the chaos iteration technology. Literature [13] proposed a secure pseudorandom number generator three-mixer. Khan et al presented a complex chaotic S-box construction method that could provide better security in terms of resistance against various attacks by deploying the 2D Henon chaotic map and skew tent map [14].…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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As the unique nonlinear component of block ciphers, Substitution box (S-box) directly affects the safety of a cryptographic system. It is important and difficult to design strong S-box that simultaneously meets multiple cryptographic criteria such as bijection, nonlinearity, strict avalanche criterion (SAC), bit independence criterion (BIC), differential probability (DP), and linear probability (LP). Though many chaotic S-boxes have been proposed, the cryptographic performance of most of them needs to be further improved. A new chaotic S-box based on the intertwining logistic map and bacterial foraging optimization is designed in this paper. It firstly iterates the intertwining logistic map to construct many S-boxes and then applies a bacterial foraging optimization algorithm to find the optimal S-box. Moreover, bacterial foraging optimization algorithm considers the nonlinearity and differential uniformity as the fitness functions in the optimization process. We experiment that the proposed S-box can effectively resist multiple types of cryptanalysis attacks.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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“…Pearson correlation coefficient measures correlation between two sequences and can be given as [34]: ±1 , and no correlation exists for C P ≈ 0. Pearson coefficient is calculated for each pair of sequences.…”

Section: Measures Of Correlation Properties Of Spreading Sequencesmentioning

confidence: 99%

“…In spread spectrum systems, two correlation functions are observed: the autocorrelation function and the cross-correlation function. Correlation properties can be evaluated using aperiodic correlation function and statistical tests [33,34]. If c X and c Y are sequences, then aperiodic correlation can be defined as [27]:…”

Section: Measures Of Correlation Properties Of Spreading Sequencesmentioning

confidence: 99%

Performance evaluation of chaotic spreading sequences on software-defined radio

Novosel

Šišul

2017

J Wireless Com Network

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In this paper, bit error performance evaluation of chaotic sequences is presented. Performance of chaotic sequences is evaluated on multiple access spread spectrum system model for USRP software defined radio. LabVIEW is used to perform numerical simulations and bit error rate analysis. Chaotic sequences of different lengths are generated using one-dimensional, two-dimensional, and three-dimensional maps. It is expected that sequences generated from complex maps will have better multiple access performance. Performance of chaotic sequences is evaluated against orthogonal sequences in multiple access scenario. Using Golay figure of merit and Pearson correlation coefficient, analysis of correlation properties and a comparison is performed on orthogonal and chaotic sequences for correlation properties comparison. The results show that chaotic sequences from two-dimensional maps have lower bit error rate than orthogonal and other chaotic sequences. Comparison of correlation properties shows that sequences with a low figure of merit and low Pearson coefficient have lower bit error rate. Those results can be used to generate chaotic sequences with desired correlation properties.

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“…Binary pseudo-random number that has good balance, correlation and linear complexity can generated with mature methods [1][2][3][4][5][6][7][8], which has been widely used in many areas such as numerical simulations, statistical mechanics, gaming industry, cryptography and communication. However, the fatal short coming of binary psedo-random number is its pseudo-random properties, which limits its application.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Physical Random Number Properties Generated by Semiconductor Super Lattices

Duan¹,

Nie²,

Xu³

et al. 2016

Proceedings of the 2016 International Conference on Education, Management and Computer Science

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Abstract. The proerties of fast physical random-number that is generated based on room-temperature chaotic oscillations in weakly coupled superlattices are investigated in detail, including the balansability, the linear complexity, the cross-correlation, and auto-correlation characteristics. Experimental and simulating reasults indicate that the ratio between the number of ones and zeros is 10001:10000 and the correlations are excellent and the linear complexity is good, which proves the physical random-number generated ased on room-temperature chaotic oscillations in weakly coupled superlattices can be used in the information secure communications effectively.

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Pseudo-random number generator based on mixing of three chaotic maps

Cited by 104 publications

References 9 publications

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Performance evaluation of chaotic spreading sequences on software-defined radio

Analysis of Physical Random Number Properties Generated by Semiconductor Super Lattices

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