Linear analysis of reduced-round CubeHash

Tomer Ashur, Orr Dunkelman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent developments in the field of cryptanalysis of hash functions has inspired NIST to announce a competition for selecting a new cryptographic hash function to join the SHA family of standards. One of the 14 second-round candidates was CubeHash designed by Daniel J. Bernstein. CubeHash is a unique hash function in the sense that it does not iterate a common compression function, and offers a structure which resembles a sponge function, even though it is not exactly a sponge function. In this paper we analyze reduced-round variants of CubeHash where the adversary controls the full 1024-bit input to reduced-round Cube- Hash and can observe its full output. We show that linear approximations with high biases exist in reduced-round variants. For example, we present an 11-round linear approximation with bias of 2-∈235, which allows distinguishing 11-round CubeHash using about 2470 queries. We also discuss the extension of this distinguisher to 12 rounds using message modification techniques. Finally, we present a linear distinguisher for 14-round CubeHash which uses about 2812 queries.

Original languageAmerican English
Title of host publicationApplied Cryptography and Network Security - 9th International Conference, ACNS 2011, Proceedings
Pages462-478
Number of pages17
DOIs
StatePublished - 2011
Event9th International Conference on Applied Cryptography and Network Security, ACNS 2011 - Nerja, Spain
Duration: 7 Jun 201110 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6715 LNCS

Conference

Conference9th International Conference on Applied Cryptography and Network Security, ACNS 2011
Country/TerritorySpain
CityNerja
Period7/06/1110/06/11

Keywords

  • CubeHash SHA-3 competition
  • Linear cryptanalysis

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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