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Collision Attack on 4-Branch, Type-2 GFN Based Hash Functions Using Sliced Biclique Cryptanalysis Technique

Authors: Megha Agrawal; Donghoon Chang; Mohona Ghosh; Somitra Kumar Sanadhya;

Collision Attack on 4-Branch, Type-2 GFN Based Hash Functions Using Sliced Biclique Cryptanalysis Technique

Abstract

In this work, we apply the sliced biclique cryptanalysis technique to show 8-round collision attack on a hash function \(H\) based on 4-branch, Type-2 Generalized Feistel Network (Type-2 GFN). This attack is generic and works on 4-branch, Type-2 GFN with any parameters including the block size, type of round function, the number of S-boxes in each round and the number of SP layers inside the round function. We first construct a 8-round distinguisher on 4-branch, Type-2 GFN and then use this distinguisher to launch 8-round collision attack on compression functions based on Matyas-Meyer-Oseas (MMO) and Miyaguchi-Preneel (MP) modes. The complexity of the attack on 128-bit compression function is \(2^{56}\). The attack can be directly translated to collision attack on MP and MMO based hash functions and pseudo-collision attack on Davies-Meyer (DM) based hash functions. When the round function \(F\) is instantiated with double SP layer, we show the first 8 round collision attack on 4-branch, Type-2 GFN with double SP layer based compression function. The previous best attack on this structure was a 6-round near collision attack shown by Sasaki at Indocrypt’12. His attack cannot be used to generate full collisions on 6-rounds and hence our result can be regarded the best so far in literature on this structure.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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