A highly nonlinear S-box based on a fractional linear transformation View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Shabieh Farwa, Tariq Shah, Lubna Idrees

ABSTRACT

We study the structure of an S-box based on a fractional linear transformation applied on the Galois field [Formula: see text]. The algorithm followed is very simple and yields an S-box with a very high ability to create confusion in the data. The cryptographic strength of the new S-box is critically analyzed by studying the properties of S-box such as nonlinearity, strict avalanche, bit independence, linear approximation probability and differential approximation probability. We also apply majority logic criterion to determine the effectiveness of our proposed S-box in image encryption applications. More... »

PAGES

1658

References to SciGraph publications

  • 2002. The Design of Rijndael, AES — The Advanced Encryption Standard in NONE
  • 2001-05-18. Perfect nonlinear S-boxes in ADVANCES IN CRYPTOLOGY — EUROCRYPT ’91
  • 1986. On the Design of S-Boxes in ADVANCES IN CRYPTOLOGY — CRYPTO ’85 PROCEEDINGS
  • 1991-01. Differential cryptanalysis of DES-like cryptosystems in JOURNAL OF CRYPTOLOGY
  • 2011. The Design of Cryptographic S-Boxes Using CSPs in PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING – CP 2011
  • 2013-07. A group theoretic approach to construct cryptographically strong substitution boxes in NEURAL COMPUTING AND APPLICATIONS
  • 1993. Constructing large cryptographically strong S-boxes in ADVANCES IN CRYPTOLOGY — AUSCRYPT '92
  • 1994. Linear Cryptanalysis Method for DES Cipher in ADVANCES IN CRYPTOLOGY — EUROCRYPT ’93
  • 2013-05. A projective general linear group based algorithm for the construction of substitution box for block ciphers in NEURAL COMPUTING AND APPLICATIONS
  • 2001-05-18. On the construction of highly nonlinear permutations in ADVANCES IN CRYPTOLOGY — EUROCRYPT’ 92
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s40064-016-3298-7

    DOI

    http://dx.doi.org/10.1186/s40064-016-3298-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1021911603

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27730020


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