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Title:
Mixderive: A New Framework of Deriving Linear Approximations and Improved Differential-Linear Distinguishers for ChaCha
Authors: Zhengting Li, Lin Ding, Xinhai Wang, Jiang Wan
Abstract:ChaCha is a well-known ARX-based cipher and has become one of the most widely used ciphers in the real world. In this paper, a systematic three-case framework called \emph{Mixderive} to find linear approximations for ChaCha is proposed. By this new framework, new linear approximations for 3.5- and 4-round ChaCha are found, which are significantly better than the existing linear approximations proposed at EUROCRYPT 2021 and ASIACRYPT 2022. These improvements confirm the effectiveness of \emph{Mixderive}. In addition, new 2- and 2.5-round linear approximations for ChaCha are found by \emph{Mixderive}. Based on these new findings, new differential-linear distinguishers for 7- and 7.5-round ChaCha256 with complexities {2^{162.28}} and {2^{247.08}} are proposed, which improve the best known distinguishers by factors of {2^{4.61}} and {2^{4.46}}, respectively. To the best of our knowledge, both cryptanalytic results are the best.
ePrint: https://eprint.iacr.org/2025/1670
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