Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1
The main options for the formation of a shared secret using synchronized artificial neural networks and possible patterns of behavior of a cryptanalyst are considered. To solve the problem of increasing the confidentiality of the generated shared secret, if it is used as a cryptographic key, it i...
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| Format: | Article |
| Language: | Russian |
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National Academy of Sciences of Belarus, the United Institute of Informatics Problems
2020-03-01
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| Series: | Informatika |
| Subjects: | |
| Online Access: | https://inf.grid.by/jour/article/view/999 |
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| _version_ | 1849335996218343424 |
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| author | M. L. Radziukevich V. F. Golikov |
| author_facet | M. L. Radziukevich V. F. Golikov |
| author_sort | M. L. Radziukevich |
| collection | DOAJ |
| description | The main options for the formation of a shared secret using synchronized artificial neural networks and possible patterns of behavior of a cryptanalyst are considered. To solve the problem of increasing the confidentiality of the generated shared secret, if it is used as a cryptographic key, it is proposed to use the mixing a certain number of results of individual synchronizations (convolution). As a mixing function, we consider the convolution of the vectors of network weights by bitwise addition modulo 2 of all the results of individual synchronizations. It is shown that the probability of success of a cryptanalyst is reduced exponentially with an increase of the number of terms in the convolution and can be chosen arbitrarily small. Moreover, the distribution law of the generated key after convolution is close to uniform and the uniformity increases with the number of terms in the convolution. |
| format | Article |
| id | doaj-art-5d7460d0f8154c4db4512a53e0bb0da2 |
| institution | Kabale University |
| issn | 1816-0301 |
| language | Russian |
| publishDate | 2020-03-01 |
| publisher | National Academy of Sciences of Belarus, the United Institute of Informatics Problems |
| record_format | Article |
| series | Informatika |
| spelling | doaj-art-5d7460d0f8154c4db4512a53e0bb0da22025-08-20T03:45:07ZrusNational Academy of Sciences of Belarus, the United Institute of Informatics ProblemsInformatika1816-03012020-03-0117110210810.37661/1816-0301-2020-17-1-102-108916Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1M. L. Radziukevich0V. F. Golikov1Scientific Production-Republican Unitary Enterprise "Research Institute for the Technical Protection of Information"Belarusian National Technical UniversityThe main options for the formation of a shared secret using synchronized artificial neural networks and possible patterns of behavior of a cryptanalyst are considered. To solve the problem of increasing the confidentiality of the generated shared secret, if it is used as a cryptographic key, it is proposed to use the mixing a certain number of results of individual synchronizations (convolution). As a mixing function, we consider the convolution of the vectors of network weights by bitwise addition modulo 2 of all the results of individual synchronizations. It is shown that the probability of success of a cryptanalyst is reduced exponentially with an increase of the number of terms in the convolution and can be chosen arbitrarily small. Moreover, the distribution law of the generated key after convolution is close to uniform and the uniformity increases with the number of terms in the convolution.https://inf.grid.by/jour/article/view/999synchronized artificial neural networksshared secretcryptographic keycompression functioncryptanalysis |
| spellingShingle | M. L. Radziukevich V. F. Golikov Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 Informatika synchronized artificial neural networks shared secret cryptographic key compression function cryptanalysis |
| title | Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| title_full | Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| title_fullStr | Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| title_full_unstemmed | Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| title_short | Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| title_sort | enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1 |
| topic | synchronized artificial neural networks shared secret cryptographic key compression function cryptanalysis |
| url | https://inf.grid.by/jour/article/view/999 |
| work_keys_str_mv | AT mlradziukevich enhancingthesecrecyofacryptographickeygeneratedusingsynchronizedartificialneuralnetworks1 AT vfgolikov enhancingthesecrecyofacryptographickeygeneratedusingsynchronizedartificialneuralnetworks1 |