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    Improving chaos-based pseudo-random generators in finite-precision arithmetic


    Tutueva, Aleksandra V., Karimov, Timur I., Moysis, Lazaros, Nepomuceno, Erivelton, Volos, Christos and Butusov, Denis N. (2021) Improving chaos-based pseudo-random generators in finite-precision arithmetic. Nonlinear Dynamics, 104 (1). pp. 727-737. ISSN 0924-090X

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    Abstract

    One of the widely-used ways in chaos-based cryptography to generate pseudo-random sequences is to use the least significant bits or digits of finite-precision numbers defined by the chaotic orbits. In this study, we show that the results obtained using such an approach are very prone to rounding errors and discretization effects. Thus, it appears that the generated sequences are close to random even when parameters correspond to non-chaotic oscillations. In this study, we confirm that the actual source of pseudo-random properties of bits in a binary representation of numbers can not be chaos, but computer simulation. We propose a technique for determining the maximum number of bits that can be used as the output of a pseudo-random sequence generator including chaos-based algorithms. The considered approach involves evaluating the difference of the binary representation of two points obtained by different numerical methods of the same order of accuracy. Experimental results show that such estimation can significantly increase the performance of the existing chaos-based generators. The obtained results can be used to reconsider and improve chaos-based cryptographic algorithms.
    Item Type: Article
    Keywords: Chaos; Pseudo-random number generator; Floating-point data type; IEEE754-2008; NIST tests;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 16815
    Identification Number: 10.1007/s11071-021-06246-0
    Depositing User: Erivelton Nepomuceno
    Date Deposited: 09 Jan 2023 12:08
    Journal or Publication Title: Nonlinear Dynamics
    Publisher: Springer
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/16815
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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