A good linear diffusion layer is a prerequisite in the design of block ciphers. Usually it is obtained by combining matrices with optimal diffusion property over the Sbox alphabet. These matrices are constructed either directly using some algebraic properties or by enumerating a search space, testing the optimal diffusion property for every element. For implementation purposes, two types of structures are considered: Structures where all the rows derive from the first row and recursive structures built from powers of companion matrices. In this paper, we propose a direct construction for new recursive-like MDS matrices. We show they are quasi-involutory in the sense that the matrix-vector product with the matrix or with its inverse can be i...
Near-MDS matrices provide better trade-offs between security and efficiency compared to construction...
Maximum Distance Separable (MDS) codes are used as diffusion layers in the design of the well known ...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...
A good linear diffusion layer is a prerequisite in the design of block ciphers. Usually it is obtain...
Best paper awardInternational audienceMDS matrices allow to build optimal linear diffusion layers in...
Abstract. MDS matrices allow to build optimal linear diffusion layers in block ciphers. However, MDS...
Abstract—This article presents a new algorithm to find MDS matrices that are well suited for use as ...
International audienceThis article presents a new algorithm to find MDS matrices that are well suite...
ISBN : 978-3-319-03514-7International audienceMany recent block ciphers use Maximum Distance Separab...
MDS matrices are used in the design of diffusion layers in many block ciphers and hash functions due...
Diffusion layers are critical components of symmetric ciphers. MDS matrices are diffusion layers of ...
The optimal branch number of MDS matrices makes them a preferred choice for designing diffusion laye...
Matrices are widely used in Block Cipher Diffusion layers, usually chosen for offering maximal branc...
This PhD focuses on the links between error correcting codes and diffusion matrices used in cryptogr...
Cette thèse s’intéresse à deux aspects de la cryptologie symétrique liés à l’utilisation de matrices...
Near-MDS matrices provide better trade-offs between security and efficiency compared to construction...
Maximum Distance Separable (MDS) codes are used as diffusion layers in the design of the well known ...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...
A good linear diffusion layer is a prerequisite in the design of block ciphers. Usually it is obtain...
Best paper awardInternational audienceMDS matrices allow to build optimal linear diffusion layers in...
Abstract. MDS matrices allow to build optimal linear diffusion layers in block ciphers. However, MDS...
Abstract—This article presents a new algorithm to find MDS matrices that are well suited for use as ...
International audienceThis article presents a new algorithm to find MDS matrices that are well suite...
ISBN : 978-3-319-03514-7International audienceMany recent block ciphers use Maximum Distance Separab...
MDS matrices are used in the design of diffusion layers in many block ciphers and hash functions due...
Diffusion layers are critical components of symmetric ciphers. MDS matrices are diffusion layers of ...
The optimal branch number of MDS matrices makes them a preferred choice for designing diffusion laye...
Matrices are widely used in Block Cipher Diffusion layers, usually chosen for offering maximal branc...
This PhD focuses on the links between error correcting codes and diffusion matrices used in cryptogr...
Cette thèse s’intéresse à deux aspects de la cryptologie symétrique liés à l’utilisation de matrices...
Near-MDS matrices provide better trade-offs between security and efficiency compared to construction...
Maximum Distance Separable (MDS) codes are used as diffusion layers in the design of the well known ...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...