Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators

Autores
Farías, Andrés Francisco; Farías, Andrés Alejandro; Montejano, Germán Antonio; Garis, Ana Gabriela; Riesco, Daniel Eduardo
Año de publicación
2025
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Various branches of science, such as cryptography, simulation and mathematics, use random or pseudo-random binary sequences. These values are obtained through the use of random or pseudo-random binary generators. These random strings must have a high period and high linear complexity, and must pass statistical randomness tests, to make sure they work. When making a generator, you need to think about all of the above things, and you need to check each step really carefully to make sure that the end result is good. If you combine cryptographic components, you might end up with an unsuitable generator. This project explains how to make a reliable Binary Generator. The generator we're proposing here is made up of two main parts: Self-Shrinking Generators, which are combined using four-variable Boolean functions and a majority function.
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Self-Shrinking Generators
Modified Self-Shrinking Generators
LFSR
Cipher
Key
Boolean function
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/191362

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network_name_str SEDICI (UNLP)
spelling Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking GeneratorsFarías, Andrés FranciscoFarías, Andrés AlejandroMontejano, Germán AntonioGaris, Ana GabrielaRiesco, Daniel EduardoCiencias InformáticasSelf-Shrinking GeneratorsModified Self-Shrinking GeneratorsLFSRCipherKeyBoolean functionVarious branches of science, such as cryptography, simulation and mathematics, use random or pseudo-random binary sequences. These values are obtained through the use of random or pseudo-random binary generators. These random strings must have a high period and high linear complexity, and must pass statistical randomness tests, to make sure they work. When making a generator, you need to think about all of the above things, and you need to check each step really carefully to make sure that the end result is good. If you combine cryptographic components, you might end up with an unsuitable generator. This project explains how to make a reliable Binary Generator. The generator we're proposing here is made up of two main parts: Self-Shrinking Generators, which are combined using four-variable Boolean functions and a majority function.Red de Universidades con Carreras en Informática2025-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf913-922http://sedici.unlp.edu.ar/handle/10915/191362enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-8258-99-7info:eu-repo/semantics/reference/hdl/10915/189846info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2026-03-31T12:41:42Zoai:sedici.unlp.edu.ar:10915/191362Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-03-31 12:41:42.842SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
title Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
spellingShingle Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
Farías, Andrés Francisco
Ciencias Informáticas
Self-Shrinking Generators
Modified Self-Shrinking Generators
LFSR
Cipher
Key
Boolean function
title_short Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
title_full Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
title_fullStr Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
title_full_unstemmed Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
title_sort Pseudo-Random Binary Generator Based on the Combination of Self-Shrinking Generators
dc.creator.none.fl_str_mv Farías, Andrés Francisco
Farías, Andrés Alejandro
Montejano, Germán Antonio
Garis, Ana Gabriela
Riesco, Daniel Eduardo
author Farías, Andrés Francisco
author_facet Farías, Andrés Francisco
Farías, Andrés Alejandro
Montejano, Germán Antonio
Garis, Ana Gabriela
Riesco, Daniel Eduardo
author_role author
author2 Farías, Andrés Alejandro
Montejano, Germán Antonio
Garis, Ana Gabriela
Riesco, Daniel Eduardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Self-Shrinking Generators
Modified Self-Shrinking Generators
LFSR
Cipher
Key
Boolean function
topic Ciencias Informáticas
Self-Shrinking Generators
Modified Self-Shrinking Generators
LFSR
Cipher
Key
Boolean function
dc.description.none.fl_txt_mv Various branches of science, such as cryptography, simulation and mathematics, use random or pseudo-random binary sequences. These values are obtained through the use of random or pseudo-random binary generators. These random strings must have a high period and high linear complexity, and must pass statistical randomness tests, to make sure they work. When making a generator, you need to think about all of the above things, and you need to check each step really carefully to make sure that the end result is good. If you combine cryptographic components, you might end up with an unsuitable generator. This project explains how to make a reliable Binary Generator. The generator we're proposing here is made up of two main parts: Self-Shrinking Generators, which are combined using four-variable Boolean functions and a majority function.
Red de Universidades con Carreras en Informática
description Various branches of science, such as cryptography, simulation and mathematics, use random or pseudo-random binary sequences. These values are obtained through the use of random or pseudo-random binary generators. These random strings must have a high period and high linear complexity, and must pass statistical randomness tests, to make sure they work. When making a generator, you need to think about all of the above things, and you need to check each step really carefully to make sure that the end result is good. If you combine cryptographic components, you might end up with an unsuitable generator. This project explains how to make a reliable Binary Generator. The generator we're proposing here is made up of two main parts: Self-Shrinking Generators, which are combined using four-variable Boolean functions and a majority function.
publishDate 2025
dc.date.none.fl_str_mv 2025-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-8258-99-7
info:eu-repo/semantics/reference/hdl/10915/189846
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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913-922
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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