Joint data and key distribution of simple, multiple, and multidimensional linear cryptanalysis test statistic and its impact to data complexity

Celine Blondeau, Kaisa Nyberg

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)

Abstract

The power of a statistical attack is inversely proportional to the number of plaintexts needed to recover information on the encryption key. By analyzing the distribution of the random variables involved in the attack, cryptographers aim to provide a good estimate of the data complexity of the attack. In this paper, we analyze the hypotheses made in simple, multiple, and multidimensional linear attacks that use either non-zero or zero correlations, and provide more accurate estimates of the data complexity of these attacks. This is achieved by taking, for the first time, into consideration the key variance of the statistic for both the right and wrong keys. For the family of linear attacks considered in this paper, we differentiate between the attacks which are performed in the known-plaintext and those in the distinct-known-plaintext model.

Original languageEnglish
Article number82
Pages (from-to) 319-349
Number of pages31
JournalDESIGNS CODES AND CRYPTOGRAPHY
Volume82
Issue number1-2
DOIs
Publication statusPublished - 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Distinct known plaintext
  • Iterated block cipher
  • Key variance
  • Known plaintext
  • Linear attack
  • Statistical model

Fingerprint Dive into the research topics of 'Joint data and key distribution of simple, multiple, and multidimensional linear cryptanalysis test statistic and its impact to data complexity'. Together they form a unique fingerprint.

Cite this