NEURAL METHODS FOR CRYPTANALYSIS

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dc.contributor.authorKhamza, Abzhan
dc.date.accessioned2022-02-07T02:24:26Z
dc.date.available2022-02-07T02:24:26Z
dc.date.issued2021-11
dc.description.abstractArtificial neural networks (ANN) are currently widely used for solving problems and tasks in various fields. In this term, cryptanalysis is no exception. New scientific approaches involving ANN in cryptographic systems studying and analyzing processes are proposed in the different stages of looking for weaknesses and breaking cryptographic algorithms. In this work, a short survey on scientific works related to the topic will be provided. Moreover, a specific ANN will be constructed for analyzing widely used asymmetric cryptosystem RSA. The model will be trained on generated training and testing data by encrypting random plaintexts. The work aims to achieve the highest performance and accuracy by trying various configurations like number of neurons, number of layers, activation functions and learning rate. Moreover, we will analyze how much data is required to train the network with good performance.en_US
dc.identifier.citationKhamza, A. (2021). Neural Methods for Cryptanalysis (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstanen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/6022
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Gated Accessen_US
dc.subjectartificial neural networksen_US
dc.subjectANNen_US
dc.subjectcryptographicen_US
dc.subjectcryptographic algorithmsen_US
dc.titleNEURAL METHODS FOR CRYPTANALYSISen_US
dc.typeMaster's thesisen_US
workflow.import.sourcescience

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