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Anomalies and Vector Space Search: Tools for S-Box Analysis

  • Xavier Bonnetain
  • Léo PerrinEmail author
  • Shizhu Tian
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11921)

Abstract

S-boxes are functions with an input so small that the simplest way to specify them is their lookup table (LUT). How can we quantify the distance between the behavior of a given S-box and that of an S-box picked uniformly at random?

To answer this question, we introduce various “anomalies”. These real numbers are such that a property with an anomaly equal to a should be found roughly once in a set of \(2^{a}\) random S-boxes. First, we present statistical anomalies based on the distribution of the coefficients in the difference distribution table, linear approximation table, and for the first time, the boomerang connectivity table.

We then count the number of S-boxes that have block-cipher like structures to estimate the anomaly associated to those. In order to recover these structures, we show that the most general tool for decomposing S-boxes is an algorithm efficiently listing all the vector spaces of a given dimension contained in a given set, and we present such an algorithm.

Combining these approaches, we conclude that all permutations that are actually picked uniformly at random always have essentially the same cryptographic properties and the same lack of structure.

Keywords

S-box Vector space search BCT Shannon effect Anomaly Boolean functions 

Notes

Acknowledgement

We thank Jérémy Jean for shepherding this paper. We also thank Florian Wartelle for fruitful discussions about vector space search, and Anne Canteaut for proofreading a first draft of this paper. The work of Xavier Bonnetain receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 714294 – acronym QUASYModo). The work of Shizhu Tian is supported by the National Science Foundation of China (No. 61772517, 61772516).

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Copyright information

© International Association for Cryptologic Research 2019

Authors and Affiliations

  1. 1.InriaParisFrance
  2. 2.Collège DoctoralSorbonne UniversitéParisFrance
  3. 3.State Key Laboratory of Information Security, Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  4. 4.School of Cyber SecurityUniversity of Chinese Academy of SciencesBeijingChina

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