Paper 2021/1105

Improved Linear Approximations of SNOW-V and SNOW-Vi

Zhen Shi, Chenhui Jin, and Yu Jin


Abstract. in this paper, we improve the results of linear approximation of SNOW-V and SNOW-Vi.We optimized the automatic search program by replacing the S-box part with accurate characterizations of the Walsh spectral of S-boxes, which results in a series of trails with higher correlations. On the basis of existing results, we investigate the common features of linear approximation trails with high correlation, and search for more trails by exhausting free masks. By summing up the correlations of trails with the same input and output masks, we get closer to the real correlation. As a result, we get a linear approximation with a correlation -2^{-47.76},which results in a correlation attack on SNOW-V and SNOW-Vi with a time complexity 2^{246:53}, data complexity 2^{237.5} and memory complexity 2^{238.77}.

Available format(s)
Secret-key cryptography
Publication info
Preprint. MINOR revision.
SNOW-VSNOW-ViCryptanalysisLinear Approxima- tionAutomatic Search.
Contact author(s)
shizhenieu @ 126 com
2021-08-31: received
Short URL
Creative Commons Attribution


      author = {Zhen Shi and Chenhui Jin and Yu Jin},
      title = {Improved Linear Approximations of SNOW-V and SNOW-Vi},
      howpublished = {Cryptology ePrint Archive, Paper 2021/1105},
      year = {2021},
      note = {\url{}},
      url = {}
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