A new variant of the matsumoto-imai cryptosystem through perturbation

Jintai Ding*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

84 Citations (Scopus)

Abstract

Though the multivariable cryptosystems first suggested by Matsumoto and Imai was defeated by the linearization method of Patarin due to the special properties of the Matsumoto-Imai (MI) cryptosystem, many variants and extensions of the MI system were suggested mainly by Patarin and his collaborators. In this paper, we propose a new variant of the MI system, which was inspired by the idea of "perturbation". This method uses a set of r (a small number) linearly independent linear functions zi = ∑j=1 n αijxji, i=1, .., r, over the variables xi, which are variables of the MI system. The perturbation is performed by adding random quadratic function of Zi to the MI systems. The difference between our idea and a very similar idea of the Hidden Field Equation and Oil-Vinegar system is that our perturbation is internal, where we do not introduce any new variables, while the Hidden Field Equation and Oil-Vinegar system is an "external" perturbation of the HFE system, where a few extra (external) new variables are introduced to perform the perturbation. A practical implementation example of 136 bits, its security analysis and efficiency analysis are presented. The attack complexity of this perturbed Matsumoto-Imai cryptosystem is estimated. Keywords: open-key, multivariable, quadratic polynomials, perturbation

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsFeng Bao, Robert Deng, Jianying Zhou
PublisherSpringer Verlag
Pages305-318
Number of pages14
ISBN (Print)3540210180, 9783540210184
DOIs
Publication statusPublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2947
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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