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The Kernel Matrix Diffie-Hellman Assumption

Autor
Morillo, M.; Rafols, C.; Villar, J.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science
Data de publicació
2016-12
Volum
10031
Pàgina inicial
729
Pàgina final
758
DOI
https://doi.org/10.1007/978-3-662-53887-6_27 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/102936 Obrir en finestra nova
URL
http://link.springer.com/chapter/10.1007/978-3-662-53887-6_27 Obrir en finestra nova
Resum
The final publication is available at link.springer.com We put forward a new family of computational assumptions, the Kernel Matrix Diffie-Hellman Assumption. Given some matrix A sampled from some distribution D, the kernel assumption says that it is hard to find “in the exponent” a nonzero vector in the kernel of A>. This family is a natural computational analogue of the Matrix Decisional Diffie-Hellman Assumption (MDDH), proposed by Escala et al. As such it allows to extend the advantages ...
Citació
Morillo, M., Rafols, C., Villar, J. The Kernel Matrix Diffie-Hellman Assumption. "Lecture notes in computer science", Desembre 2016, vol. 10031, p. 729-758.
Paraules clau
Black-Box Reductions, Computational Problems, Matrix Assumptions, Structure Preserving Cryptography
Grup de recerca
MAK - Matemàtica Aplicada a la Criptografia

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