Diffusion layers are critical components of symmetric ciphers. MDS matrices are diffusion layers of maximal branch number which have been used in various symmetric ciphers. In this article, we examine decomposition of cyclic matrices from mathematical viewpoint and based on that, we present new cyclic MDS matrices. From the aspect of implementation, the proposed matrices have lower implementation costs both in software and hardware, compared to what is presented in cryptographic literature, up to our knowledge
Abstract. MDS matrices allow to build optimal linear diffusion layers in block ciphers. However, MDS...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...
Abstract. Diusion layers are crucial components of sym-metric ciphers. These components, along with ...
A good linear diffusion layer is a prerequisite in the design of block ciphers. Usually it is obtain...
The primary intention of this thesis is to generate lightened Maximum Distance Separable (MDS) matri...
Best paper awardInternational audienceMDS matrices allow to build optimal linear diffusion layers in...
Cette thèse s’intéresse à deux aspects de la cryptologie symétrique liés à l’utilisation de matrices...
Abstract—This article presents a new algorithm to find MDS matrices that are well suited for use as ...
This PhD focuses on the links between error correcting codes and diffusion matrices used in cryptogr...
MDS matrices are used as building blocks of diffusion layers in block ciphers, and XOR count is a me...
Maximum distance separable (MDS) matrices have applications not only in coding theory but also are o...
The 4x4 MDS matrix over F2 is widely used in the design of block cipher\u27s linear diffusion layer...
International audienceThis article presents a new algorithm to find MDS matrices that are well suite...
Near-MDS matrices provide better trade-offs between security and efficiency compared to construction...
Matrices are widely used in Block Cipher Diffusion layers, usually chosen for offering maximal branc...
Abstract. MDS matrices allow to build optimal linear diffusion layers in block ciphers. However, MDS...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...
Abstract. Diusion layers are crucial components of sym-metric ciphers. These components, along with ...
A good linear diffusion layer is a prerequisite in the design of block ciphers. Usually it is obtain...
The primary intention of this thesis is to generate lightened Maximum Distance Separable (MDS) matri...
Best paper awardInternational audienceMDS matrices allow to build optimal linear diffusion layers in...
Cette thèse s’intéresse à deux aspects de la cryptologie symétrique liés à l’utilisation de matrices...
Abstract—This article presents a new algorithm to find MDS matrices that are well suited for use as ...
This PhD focuses on the links between error correcting codes and diffusion matrices used in cryptogr...
MDS matrices are used as building blocks of diffusion layers in block ciphers, and XOR count is a me...
Maximum distance separable (MDS) matrices have applications not only in coding theory but also are o...
The 4x4 MDS matrix over F2 is widely used in the design of block cipher\u27s linear diffusion layer...
International audienceThis article presents a new algorithm to find MDS matrices that are well suite...
Near-MDS matrices provide better trade-offs between security and efficiency compared to construction...
Matrices are widely used in Block Cipher Diffusion layers, usually chosen for offering maximal branc...
Abstract. MDS matrices allow to build optimal linear diffusion layers in block ciphers. However, MDS...
International audienceThis paper investigates large linear mappings with very good diffusion and eff...
Abstract. Diusion layers are crucial components of sym-metric ciphers. These components, along with ...