Zobrazeno 1 - 10
of 163
pro vyhledávání: '"Vladimir Shpilrain"'
Autor:
Vladimir Shpilrain
Publikováno v:
Communications in Algebra. 51:799-806
Autor:
Giovanni Di Crescenzo, Matluba Khodjaeva, Ta Chen, Rajesh Krishnan, David Shur, Delaram Kahrobaei, Vladimir Shpilrain
Publikováno v:
Innovative Security Solutions for Information Technology and Communications ISBN: 9783031326356
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf0cd3c15866254a2ea4ed50b416ba0a
https://doi.org/10.1007/978-3-031-32636-3_5
https://doi.org/10.1007/978-3-031-32636-3_5
Publikováno v:
Journal of Mathematical Cryptology. 17
In this article, we analyze two digital signature schemes, proposed in Moldovyan et al., that use finite noncommutative associative algebras as underlying platforms. We prove that these schemes do not possess the claimed property of being quantum saf
Autor:
Vladimir Shpilrain, Delaram Kahrobaei
Publikováno v:
International Journal of Computer Mathematics: Computer Systems Theory. 6:381-385
Autor:
Vladimir Shpilrain
Publikováno v:
Journal of Mathematical Sciences. 257:919-925
We reflect on how to define the complexity of a matrix and how to sample a random invertible matrix. We also discuss a related issue of complexity of algorithms in matrix groups.
Publikováno v:
Journal of Mathematical Cryptology, Vol 14, Iss 1, Pp 438-459 (2020)
Many public-key cryptosystems and, more generally, cryptographic protocols, use group exponentiations as important primitive operations. To expand the applicability of these solutions to computationally weaker devices, it has been advocated that a co
Publikováno v:
Mathematics in Computer Science. 14:641-656
Group exponentiation is an important and relatively expensive operation used in many public-key cryptosystems and, more generally, cryptographic protocols. To expand the applicability of these solutions to computationally weaker devices, it has been
Publikováno v:
Developments in Language Theory ISBN: 9783031055775
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::caef24bb074467290c28b0a8c853486e
https://doi.org/10.1007/978-3-031-05578-2_3
https://doi.org/10.1007/978-3-031-05578-2_3
Autor:
Giovanni Di Crescenzo, Matluba Khodjaeva, Vladimir Shpilrain, Delaram Kahrobaei, Rajesh Krishnan
Publikováno v:
2021 14th International Conference on Security of Information and Networks (SIN).
Publikováno v:
Computers in Biology and Medicine. 105:144-150
Clinicians would benefit from access to predictive models for diagnosis, such as classification of tumors as malignant or benign, without compromising patients' privacy. In addition, the medical institutions and companies who own these medical inform