[Resource Topic] 2023/1266: Automatic Preimage Attack Framework on \ascon Using a Linearize-and-Guess Approach

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Automatic Preimage Attack Framework on \ascon Using a Linearize-and-Guess Approach

Authors: Huina Li, Le He, Shiyao Chen, Jian Guo, Weidong Qiu


\ascon is the final winner of the lightweight cryptography standardization competition (2018-2023).
In this paper, we focus on preimage attacks against round-reduced \ascon.
The preimage attack framework, utilizing the linear structure with the allocating model, was initially proposed by Guo \textit{et al.} at ASIACRYPT 2016 and subsequently improved by Li \textit{et al.} at EUROCRYPT 2019, demonstrating high effectiveness in breaking the preimage resistance of \keccak.
In this paper, we extend this preimage attack framework to \ascon from two aspects. Firstly, we propose a linearize-and-guess approach by analyzing the algebraic properties of the \ascon permutation. As a result, the complexity of finding a preimage for 2-round \ascon-\xof with a 64-bit hash value can be significantly reduced from 2^{39} guesses to 2^{27.56} guesses.
To support the effectiveness of our approach, we find an actual preimage of all ‘0’ hash in practical time.
Secondly, we develop a SAT-based automatic preimage attack framework using the linearize-and-guess approach, which is efficient to search for the optimal structures exhaustively. Consequently, we present the best theoretical preimage attacks on 3-round and 4-round \ascon-\xof so far.

ePrint: https://eprint.iacr.org/2023/1266

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