Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance
Encryption algorithms based on block ciphers are among the most widely adopted solutions for providing information security. Over the years, a variety of methods have been proposed to evaluate the robustness of these algorithms to different types of security attacks. One of the most effective analys...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10015012/ |
| _version_ | 1797902257170153472 |
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| author | Vincenzo Agate Federico Concone Alessandra De Paola Pierluca Ferraro Giuseppe Lo Re Marco Morana |
| author_facet | Vincenzo Agate Federico Concone Alessandra De Paola Pierluca Ferraro Giuseppe Lo Re Marco Morana |
| author_sort | Vincenzo Agate |
| collection | DOAJ |
| description | Encryption algorithms based on block ciphers are among the most widely adopted solutions for providing information security. Over the years, a variety of methods have been proposed to evaluate the robustness of these algorithms to different types of security attacks. One of the most effective analysis techniques is differential cryptanalysis, whose aim is to study how variations in the input propagate on the output. In this work we address the modeling of differential attacks to block cipher algorithms by defining a Bayesian framework that allows a probabilistic estimation of the secret key. In order to prove the validity of the proposed approach, we present as case study a differential attack to the Data Encryption Standard (DES) which, despite being one of the methods that has been most thoroughly analyzed, is still of great interest to the scientific community since its vulnerabilities may have implications on other ciphers. |
| first_indexed | 2024-04-10T09:14:49Z |
| format | Article |
| id | doaj.art-ecf4011b4cc240cca1067ee3e6be5d66 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T09:14:49Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-ecf4011b4cc240cca1067ee3e6be5d662023-02-21T00:02:45ZengIEEEIEEE Access2169-35362023-01-01114809482010.1109/ACCESS.2023.323624010015012Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES InstanceVincenzo Agate0https://orcid.org/0000-0002-3326-8500Federico Concone1https://orcid.org/0000-0001-7638-3624Alessandra De Paola2https://orcid.org/0000-0002-7340-1847Pierluca Ferraro3https://orcid.org/0000-0003-1574-1111Giuseppe Lo Re4https://orcid.org/0000-0002-8217-2230Marco Morana5https://orcid.org/0000-0002-5963-6236Department of Engineering, University of Palermo, Palermo, ItalyDepartment of Engineering, University of Palermo, Palermo, ItalyDepartment of Engineering, University of Palermo, Palermo, ItalyDepartment of Engineering, University of Palermo, Palermo, ItalyDepartment of Engineering, University of Palermo, Palermo, ItalyDepartment of Engineering, University of Palermo, Palermo, ItalyEncryption algorithms based on block ciphers are among the most widely adopted solutions for providing information security. Over the years, a variety of methods have been proposed to evaluate the robustness of these algorithms to different types of security attacks. One of the most effective analysis techniques is differential cryptanalysis, whose aim is to study how variations in the input propagate on the output. In this work we address the modeling of differential attacks to block cipher algorithms by defining a Bayesian framework that allows a probabilistic estimation of the secret key. In order to prove the validity of the proposed approach, we present as case study a differential attack to the Data Encryption Standard (DES) which, despite being one of the methods that has been most thoroughly analyzed, is still of great interest to the scientific community since its vulnerabilities may have implications on other ciphers.https://ieeexplore.ieee.org/document/10015012/Differential cryptanalysisBayesian networksprobabilistic inferenceDES |
| spellingShingle | Vincenzo Agate Federico Concone Alessandra De Paola Pierluca Ferraro Giuseppe Lo Re Marco Morana Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance IEEE Access Differential cryptanalysis Bayesian networks probabilistic inference DES |
| title | Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance |
| title_full | Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance |
| title_fullStr | Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance |
| title_full_unstemmed | Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance |
| title_short | Bayesian Modeling for Differential Cryptanalysis of Block Ciphers: A DES Instance |
| title_sort | bayesian modeling for differential cryptanalysis of block ciphers a des instance |
| topic | Differential cryptanalysis Bayesian networks probabilistic inference DES |
| url | https://ieeexplore.ieee.org/document/10015012/ |
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