Indifferentiability of confusion-diffusion networks

Yevgeniy Dodis, Martijn Stam, John Steinberger, Tianren Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We show the first positive results for the indifferentiability security of the confusion-diffusion networks (which are extensively used in the design of block ciphers and hash functions). In particular, our result shows that a constant number of confusion-diffusion rounds is sufficient to extend the domain of a public random permutation.

Original languageEnglish (US)
Title of host publicationAdvances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings
PublisherSpringer Verlag
Pages679-704
Number of pages26
Volume9666
ISBN (Print)9783662498958
DOIs
StatePublished - 2016
Event35th Annual International Conference on Theory and Applications of Cryptographic Techniques, EUROCRYPT 2016 - Vienna, Austria
Duration: May 8 2016May 12 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9666
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other35th Annual International Conference on Theory and Applications of Cryptographic Techniques, EUROCRYPT 2016
CountryAustria
CityVienna
Period5/8/165/12/16

Fingerprint

Random Permutation
Block Ciphers
Hash functions
Hash Function
Sufficient
Design

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Dodis, Y., Stam, M., Steinberger, J., & Liu, T. (2016). Indifferentiability of confusion-diffusion networks. In Advances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings (Vol. 9666, pp. 679-704). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9666). Springer Verlag. https://doi.org/10.1007/978-3-662-49896-5_24

Indifferentiability of confusion-diffusion networks. / Dodis, Yevgeniy; Stam, Martijn; Steinberger, John; Liu, Tianren.

Advances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Vol. 9666 Springer Verlag, 2016. p. 679-704 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9666).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dodis, Y, Stam, M, Steinberger, J & Liu, T 2016, Indifferentiability of confusion-diffusion networks. in Advances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. vol. 9666, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9666, Springer Verlag, pp. 679-704, 35th Annual International Conference on Theory and Applications of Cryptographic Techniques, EUROCRYPT 2016, Vienna, Austria, 5/8/16. https://doi.org/10.1007/978-3-662-49896-5_24
Dodis Y, Stam M, Steinberger J, Liu T. Indifferentiability of confusion-diffusion networks. In Advances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Vol. 9666. Springer Verlag. 2016. p. 679-704. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-662-49896-5_24
Dodis, Yevgeniy ; Stam, Martijn ; Steinberger, John ; Liu, Tianren. / Indifferentiability of confusion-diffusion networks. Advances in Cryptology - EUROCRYPT 2016 - 35th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Vol. 9666 Springer Verlag, 2016. pp. 679-704 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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