Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System

This paper examines the practical implementation of the Montgomery algorithm in asymmetric cryptosystems using the Residue Number System. Residue Number System enables concurrent computations of additions and multiplications across multiple channels, eliminating the need for bit carrying between the...

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Главные авторы:	Lutsenko, V. V., Луценко, В. В.
Формат:	Статья
Язык:	English
Опубликовано:	Springer Science and Business Media Deutschland GmbH 2024
Темы:	Akushsky core function Residue number system (RNS) Error detection Neural networks
Online-ссылка:	https://dspace.ncfu.ru/handle/123456789/29304
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spelling	ir-123456789-293042024-12-04T12:08:36Z Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System Lutsenko, V. V. Луценко, В. В. Akushsky core function Residue number system (RNS) Error detection Neural networks This paper examines the practical implementation of the Montgomery algorithm in asymmetric cryptosystems using the Residue Number System. Residue Number System enables concurrent computations of additions and multiplications across multiple channels, eliminating the need for bit carrying between them. Base extension is an essential aspect of RNS implementation for asymmetric cryptosystems. In this research, we introduce a novel method for conducting base expansion using the Akushsky Core Function. Our findings show that this innovative technique significantly reduces computational expenses compared to existing methods. The proposed approach enhances the efficiency of the Montgomery algorithm and advances the field of asymmetric cryptography by introducing a streamlined process for base expansion in the context of Residue Number Systems. 2024-12-04T12:07:12Z 2024-12-04T12:07:12Z 2024 Статья Lutsenko, V., Zgonnikov, M. Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System // Lecture Notes in Networks and Systems. - 2024. - 863 LNNS. - pp. 194-206. - DOI: 10.1007/978-3-031-72171-7_20 https://dspace.ncfu.ru/handle/123456789/29304 en Lecture Notes in Networks and Systems application/pdf Springer Science and Business Media Deutschland GmbH
institution	СКФУ
collection	Репозиторий
language	English
topic	Akushsky core function Residue number system (RNS) Error detection Neural networks
spellingShingle	Akushsky core function Residue number system (RNS) Error detection Neural networks Lutsenko, V. V. Луценко, В. В. Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
description	This paper examines the practical implementation of the Montgomery algorithm in asymmetric cryptosystems using the Residue Number System. Residue Number System enables concurrent computations of additions and multiplications across multiple channels, eliminating the need for bit carrying between them. Base extension is an essential aspect of RNS implementation for asymmetric cryptosystems. In this research, we introduce a novel method for conducting base expansion using the Akushsky Core Function. Our findings show that this innovative technique significantly reduces computational expenses compared to existing methods. The proposed approach enhances the efficiency of the Montgomery algorithm and advances the field of asymmetric cryptography by introducing a streamlined process for base expansion in the context of Residue Number Systems.
format	Статья
author	Lutsenko, V. V. Луценко, В. В.
author_facet	Lutsenko, V. V. Луценко, В. В.
author_sort	Lutsenko, V. V.
title	Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
title_short	Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
title_full	Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
title_fullStr	Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
title_full_unstemmed	Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
title_sort	investigation of neural network methods for error detection and correction in the residue number system
publisher	Springer Science and Business Media Deutschland GmbH
publishDate	2024
url	https://dspace.ncfu.ru/handle/123456789/29304
work_keys_str_mv	AT lutsenkovv investigationofneuralnetworkmethodsforerrordetectionandcorrectionintheresiduenumbersystem AT lucenkovv investigationofneuralnetworkmethodsforerrordetectionandcorrectionintheresiduenumbersystem
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Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System

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