Conditional correlation attack on nonlinear filter generators

Sangjin Lee, Seongtaek Chee, Sangjoon Park, Sungmo Park

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

13 Citations (Scopus)

Abstract

In this paper, the optimum correlation attack recently introduced by R. Anderson is improved to be applicable to most of the nonlinear filter generators. We propose a conditional correlation attack by introducing a novel notion of the conditional linear approximation. It is shown that there are always strong correlations between key stream sequences and their corresponding input bits or their linear combinations. Finally, we suggest a practical attacking method that can be applied to most of the nonlinear filter generators.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages360-367
Number of pages8
Volume1163
ISBN (Print)9783540618720
Publication statusPublished - 1996
Externally publishedYes
EventInternational Conference on the Theory and Applications of Cryptology and Information Security, ASIACRYPT 1996 - Kyongju, Korea, Republic of
Duration: 1996 Nov 31996 Nov 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1163
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Conference on the Theory and Applications of Cryptology and Information Security, ASIACRYPT 1996
CountryKorea, Republic of
CityKyongju
Period96/11/396/11/7

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Conditional correlation attack on nonlinear filter generators'. Together they form a unique fingerprint.

  • Cite this

    Lee, S., Chee, S., Park, S., & Park, S. (1996). Conditional correlation attack on nonlinear filter generators. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1163, pp. 360-367). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1163). Springer Verlag.