Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/29304
Title: Investigation of Neural Network Methods for Error Detection and Correction in the Residue Number System
Authors: Lutsenko, V. V.
Луценко, В. В.
Keywords: Akushsky core function;Residue number system (RNS);Error detection;Neural networks
Issue Date: 2024
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: 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
Series/Report no.: Lecture Notes in Networks and Systems
Abstract: 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.
URI: https://dspace.ncfu.ru/handle/123456789/29304
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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