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Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression
In recent years, side-channel analysis technology has been one of the greatest threats to information security. SCA decrypts the key information in the encryption device by establishing an appropriate leakage model. As one of many leakage models, the XOR operation leakage proposed by linear regressi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048069/ https://www.ncbi.nlm.nih.gov/pubmed/36981393 http://dx.doi.org/10.3390/e25030505 |
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author | Jiang, Zijing Ding, Qun |
author_facet | Jiang, Zijing Ding, Qun |
author_sort | Jiang, Zijing |
collection | PubMed |
description | In recent years, side-channel analysis technology has been one of the greatest threats to information security. SCA decrypts the key information in the encryption device by establishing an appropriate leakage model. As one of many leakage models, the XOR operation leakage proposed by linear regression has typical representative significance in side-channel analysis. However, linear regression may have the problem of irreversibility of a singular matrix in the modeling stage of template analysis and the problem of poor data fit in the template analysis after the cryptographic algorithm is masked. Therefore, this paper proposes a second-order template analysis method based on orthogonal transformation nonlinear regression. The irreversibility of a singular matrix and the inaccuracy of the model are solved by orthogonal transformation and adding a negative direction to the calculation of the regression coefficient matrix. In order to verify the data fitting effect of the constructed template, a comparative experiment of template analysis based on regression, Gaussian, and clustering was carried out on SAKURA-G. The experimental results show that the second-order template analysis based on orthogonal transformation nonlinear regression can complete key recovery without sacrificing the performance of regression estimation. Under the condition of high noise and high order template analysis, the established template has good universality. |
format | Online Article Text |
id | pubmed-10048069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100480692023-03-29 Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression Jiang, Zijing Ding, Qun Entropy (Basel) Article In recent years, side-channel analysis technology has been one of the greatest threats to information security. SCA decrypts the key information in the encryption device by establishing an appropriate leakage model. As one of many leakage models, the XOR operation leakage proposed by linear regression has typical representative significance in side-channel analysis. However, linear regression may have the problem of irreversibility of a singular matrix in the modeling stage of template analysis and the problem of poor data fit in the template analysis after the cryptographic algorithm is masked. Therefore, this paper proposes a second-order template analysis method based on orthogonal transformation nonlinear regression. The irreversibility of a singular matrix and the inaccuracy of the model are solved by orthogonal transformation and adding a negative direction to the calculation of the regression coefficient matrix. In order to verify the data fitting effect of the constructed template, a comparative experiment of template analysis based on regression, Gaussian, and clustering was carried out on SAKURA-G. The experimental results show that the second-order template analysis based on orthogonal transformation nonlinear regression can complete key recovery without sacrificing the performance of regression estimation. Under the condition of high noise and high order template analysis, the established template has good universality. MDPI 2023-03-15 /pmc/articles/PMC10048069/ /pubmed/36981393 http://dx.doi.org/10.3390/e25030505 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jiang, Zijing Ding, Qun Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title | Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title_full | Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title_fullStr | Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title_full_unstemmed | Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title_short | Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression |
title_sort | second-order side-channel analysis based on orthogonal transform nonlinear regression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10048069/ https://www.ncbi.nlm.nih.gov/pubmed/36981393 http://dx.doi.org/10.3390/e25030505 |
work_keys_str_mv | AT jiangzijing secondordersidechannelanalysisbasedonorthogonaltransformnonlinearregression AT dingqun secondordersidechannelanalysisbasedonorthogonaltransformnonlinearregression |