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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Format: | Article |
Language: | Russian |
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Educational institution «Belarusian State University of Informatics and Radioelectronics»
2019-06-01
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Series: | Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki |
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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. |
first_indexed | 2024-04-10T03:14:47Z |
format | Article |
id | doaj.art-a4282ca15dbe4fdc96f4270fe5ed363d |
institution | Directory Open Access Journal |
issn | 1729-7648 |
language | Russian |
last_indexed | 2024-04-10T03:14:47Z |
publishDate | 2019-06-01 |
publisher | Educational institution «Belarusian State University of Informatics and Radioelectronics» |
record_format | Article |
series | Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki |
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 |
work_keys_str_mv | AT vfgolikov commonsecretkeyderivationbasedonsynchronizedartificialneuronalnetworksusingmultispeedweightedcoefficientscorrection AT nvbrych commonsecretkeyderivationbasedonsynchronizedartificialneuronalnetworksusingmultispeedweightedcoefficientscorrection |