An innovative approach based on optimization for the determination of initial conditions of continuous-time chaotic system as a random number generator

dc.contributor.authorYildirim, Gokce
dc.contributor.authorTanyildizi, Erkan
dc.date.accessioned2026-08-12T18:08:26Z
dc.date.issued2023
dc.departmentFırat Üniversitesi
dc.description.abstractSecurity has been one of the important problems in the processing, storage and transmission of information. The transfer of information to virtual environments with technological developments has made it necessary to examine the concept of security with different dimensions. Data security can be achieved to a great extent by using randomly generated unpredictable bit sequences in encryption. In this study, approximately 1,000,000 random bits were generated for use in computer science. The Mode2(x) method and the unpredictable nature of chaotic systems are used for random number generation. With this hybrid structure used in the study, it is aimed to gain a different perspective to future studies. However, it is known that the sensitivity of chaotic systems to initial conditions is very high. The most important contribution of the study to the literature is that the initial conditions were determined using optimization algorithms. In this study, Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) were used to calculate the initial conditions. To the authors' knowledge, this is the first study to use optimization to determine initial conditions for continuous-time chaotic systems. NIST SP 800-22 Statistical Test Suite was used to analyze the reliability of the generated random bits. It was seen that the proposed method passed all statistical tests successfully (100 %). Histogram and floating frequency analysis were used for the analysis of random numbers obtained from the generated bits. Histogram plots showed uniform distribution. It is seen that there is a homogeneous distribution in the sliding frequency analysis.
dc.description.sponsorshipSci-entific and Technological Research Council of Turkey (TUBITAK) [121E210]
dc.description.sponsorshipAcknowledgements We would like to thank you. The study was supported by the Sci-entific and Technological Research Council of Turkey (TUBITAK) with the project number 121E210.
dc.identifier.doi10.1016/j.chaos.2023.113548
dc.identifier.issn0960-0779
dc.identifier.issn1873-2887
dc.identifier.orcid0000-0002-1863-1578
dc.identifier.orcid0000-0003-2973-9389
dc.identifier.scopus2-s2.0-85162191329
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.chaos.2023.113548
dc.identifier.urihttps://hdl.handle.net/11508/63089
dc.identifier.volume172
dc.identifier.wosWOS:001018524200001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofChaos Solitons & Fractals
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectChaotic systems
dc.subjectOptimization
dc.subjectRandom number generator
dc.subjectNIST
dc.titleAn innovative approach based on optimization for the determination of initial conditions of continuous-time chaotic system as a random number generator
dc.typeArticle

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