New block cipher DONUT using pairwise perfect decorrelation

Dong Hyeon Cheon, Sangjin Lee, Jong In Lim, Sung Jae Lee

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

1 Citation (Scopus)

Abstract

Vaudenay[1] proposed a new way of protecting block ciphers against classes of attacks, which was based on the notion of decorrelation. He also suggested two block cipher families COCONUT and PEANUT. Wagner[2] suggested a new differential-style attack called boomerang attack and cryptanalysed COCONUT’98. In this paper we will suggest a new block cipher called DONUT which is made by two pairwise perfect decorrelation modules. DONUT is secure against boomerang attack.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages250-258
Number of pages9
Volume1977
ISBN (Print)3540414525, 9783540414520
Publication statusPublished - 2000
Event1st International Conference in Cryptology in India, INDOCRYPT 2000 - Calcutta, India
Duration: 2000 Dec 102000 Dec 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1977
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other1st International Conference in Cryptology in India, INDOCRYPT 2000
CountryIndia
CityCalcutta
Period00/12/1000/12/13

Fingerprint

Block Cipher
Pairwise
Attack
Block Ciphers
Module

Keywords

  • Block cipher
  • Decorrelation
  • Differential Cryptanalysis(DC)
  • Linear Cryptanalysis(LC)

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Cheon, D. H., Lee, S., Lim, J. I., & Lee, S. J. (2000). New block cipher DONUT using pairwise perfect decorrelation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1977, pp. 250-258). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1977). Springer Verlag.

New block cipher DONUT using pairwise perfect decorrelation. / Cheon, Dong Hyeon; Lee, Sangjin; Lim, Jong In; Lee, Sung Jae.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1977 Springer Verlag, 2000. p. 250-258 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1977).

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

Cheon, DH, Lee, S, Lim, JI & Lee, SJ 2000, New block cipher DONUT using pairwise perfect decorrelation. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1977, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1977, Springer Verlag, pp. 250-258, 1st International Conference in Cryptology in India, INDOCRYPT 2000, Calcutta, India, 00/12/10.
Cheon DH, Lee S, Lim JI, Lee SJ. New block cipher DONUT using pairwise perfect decorrelation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1977. Springer Verlag. 2000. p. 250-258. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Cheon, Dong Hyeon ; Lee, Sangjin ; Lim, Jong In ; Lee, Sung Jae. / New block cipher DONUT using pairwise perfect decorrelation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1977 Springer Verlag, 2000. pp. 250-258 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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