On enumeration of polynomial equivalence classes and their application to MPKC - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Finite Fields and Their Applications Année : 2012

On enumeration of polynomial equivalence classes and their application to MPKC

Dongdai Lin
  • Fonction : Auteur
  • PersonId : 935335
Jean-Charles Faugère
Ludovic Perret
  • Fonction : Auteur
  • PersonId : 935330
  • IdRef : 123278864

Résumé

The Isomorphism of Polynomials (IP) is one of the most fundamental problems in multivariate public key cryptography (MPKC). In this paper, we introduce a new framework to study the counting problem associated to IP. Namely, we present tools of finite geometry allowing to investigate the counting problem associated to IP. Precisely, we focus on enumerating or estimating the number of isomorphism equivalence classes of homogeneous quadratic polynomial systems. These problems are equivalent to finding the scale of the key space of a multivariate cryptosystem and the total number of different multivariate cryptographic schemes respectively, which might impact the security and the potential capability of MPKC. We also consider their applications in the analysis of a specific multivariate public key cryptosystem. Our results not only answer how many cryptographic schemes can be derived from monomials and how big the key space is for a fixed scheme, but also show that quite many HFE cryptosystems are equivalent to a Matsumoto-Imai scheme.
Fichier principal
Vignette du fichier
FFA2011.pdf (212.97 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00776073 , version 1 (15-01-2013)

Identifiants

Citer

Dongdai Lin, Jean-Charles Faugère, Ludovic Perret, Tianze Wang. On enumeration of polynomial equivalence classes and their application to MPKC. Finite Fields and Their Applications, 2012, 18 (2), pp.283-302. ⟨10.1016/j.ffa.2011.09.001⟩. ⟨hal-00776073⟩
174 Consultations
176 Téléchargements

Altmetric

Partager

More