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Quantum Algorithms for Fast Correlation Attacks on LFSR-Based Stream Ciphers

Authors:
Akinori Hosoyamada , NTT Social Informatics Laboratories
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Presentation: Slides
Conference: ASIACRYPT 2024
Abstract: This paper presents quantum algorithms for fast correlation attacks, one of the most powerful techniques for cryptanalysis on LFSR-based stream ciphers in the classical setting. Typical fast correlation attacks recover a value related to the initial state of the underlying LFSR by solving a decoding problem on a binary linear code with the Fast Walsh-Hadamard Transform (FWHT). Applying the FWHT on a function in the classical setting is mathematically equivalent to applying the Hadamard transform on the corresponding state in quantum computation. While the classical FWHT on a function with $\ell$-bit inputs requires $O(\ell 2^\ell)$ operations, the Hadamard transform on $\ell$-qubit states requires only a parallel application of $O(\ell)$ basic gates. This difference leads to the exponential speed-up by some quantum algorithms, including Simon's period finding algorithm. Given these facts, the question naturally arises of whether a quantum speedup can also be achieved for fast correlations by replacing the classical FWHT with the quantum Hadamard transform. We show quantum algorithms achieving speed-up in such a way, introducing a new attack model in the Q2 setting. The new model endows adversaries with a quite strong power, but we demonstrate its feasibility by showing that certain members of the ChaCha and Salsa20 families will likely be secure in the new model. Our attack exploits the link between LFSRs' state update and multiplication in a fine field to apply Shor's algorithm for the discrete logarithm problem. We apply our attacks on SNOW 2.0, SNOW 3G, and Sosemanuk, observing a large speed-up from classical attacks.
BibTeX
@inproceedings{asiacrypt-2024-34638,
  title={Quantum Algorithms for Fast Correlation Attacks on LFSR-Based Stream Ciphers},
  publisher={Springer-Verlag},
  author={Akinori Hosoyamada},
  year=2024
}