publication . Article . 2020

Enhancing the secrecy of a cryptographic key generated using synchronized artificial neural networks1

M. L. Radziukevich; V. F. Golikov;
Open Access Russian
  • Published: 01 Mar 2020 Journal: Informatika, volume 17, issue 1, pages 102-108 (issn: 1816-0301, Copyright policy)
  • Publisher: The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Abstract
<jats:p>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...
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Persistent Identifiers

doi: 10.37661/1816-0301-2020-17-1-102-108

Subjects
arXiv: Computer Science::Cryptography and Security
free text keywords: synchronized artificial neural networks, shared secret, cryptographic key, compression function, cryptanalysis, lcsh:Electronic computers. Computer science, lcsh:QA75.5-76.95, Key (cryptography), Secrecy, Computer security, computer.software_genre, computer, Computer science
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