Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction

It's possible to use artificial neuronal networks for secret key derivation. Transneuronal statistical weights of synchronized artificial neuronal networks will be used as a secret key. Proposed algorithm allows to decrease synchronization time meaningfully. Proposed correction rule helps to so...

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Bibliographic Details
Main Authors: V. F. Golikov, N. V. Brych
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2019-06-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
Subjects:
Online Access:https://doklady.bsuir.by/jour/article/view/530
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author V. F. Golikov
N. V. Brych
author_facet V. F. Golikov
N. V. Brych
author_sort V. F. Golikov
collection DOAJ
description It's possible to use artificial neuronal networks for secret key derivation. Transneuronal statistical weights of synchronized artificial neuronal networks will be used as a secret key. Proposed algorithm allows to decrease synchronization time meaningfully. Proposed correction rule helps to solve the problem of statistical weights binding while synchronizing artificial neuronal networks.
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last_indexed 2024-04-10T03:14:47Z
publishDate 2019-06-01
publisher Educational institution «Belarusian State University of Informatics and Radioelectronics»
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spelling doaj.art-a4282ca15dbe4fdc96f4270fe5ed363d2023-03-13T07:33:15ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482019-06-01055459529Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients CorrectionV. F. Golikov0N. V. Brych1Белорусский государственный университет информатики и радиоэлектроникиБелорусский государственный университет информатики и радиоэлектроникиIt's possible to use artificial neuronal networks for secret key derivation. Transneuronal statistical weights of synchronized artificial neuronal networks will be used as a secret key. Proposed algorithm allows to decrease synchronization time meaningfully. Proposed correction rule helps to solve the problem of statistical weights binding while synchronizing artificial neuronal networks.https://doklady.bsuir.by/jour/article/view/530искусственные нейронные сетикриптографиясекретный ключ
spellingShingle V. F. Golikov
N. V. Brych
Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
искусственные нейронные сети
криптография
секретный ключ
title Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
title_full Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
title_fullStr Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
title_full_unstemmed Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
title_short Common Secret Key Derivation Based on Synchronized Artificial Neuronal Networks Using Multispeed Weighted Coefficients Correction
title_sort common secret key derivation based on synchronized artificial neuronal networks using multispeed weighted coefficients correction
topic искусственные нейронные сети
криптография
секретный ключ
url https://doklady.bsuir.by/jour/article/view/530
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AT nvbrych commonsecretkeyderivationbasedonsynchronizedartificialneuronalnetworksusingmultispeedweightedcoefficientscorrection