Novel normalization technique for chaotic Pseudo-random number generators based on semi-implicit ODE solvers

The paper considers the general structure of Pseudo-random binary sequence generator based on the numerical solution of chaotic differential equations. The proposed generator architecture divides the generation process in two stages: numerical simulation of the chaotic system and converting the resulting sequence to a binary form. The new method of calculation of normalization factor is applied to the conversion of state variables values to the binary sequence. Numerical solution of chaotic ODEs is implemented using semi-implicit symmetric composition D-method. Experimental study considers Thomas and Rössler attractors as test chaotic systems. Properties verification for the output sequences of generators is carried out using correlation analysis methods and NIST statistical test suite. It is shown that output sequences of investigated generators have statistical and correlation characteristics that are specific for the random sequences. The obtained results can be used in cryptography applications as well as in secure communication systems design.

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