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Several MILP-Aided Attacks Against SNOW 2.0

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Book cover Cryptology and Network Security (CANS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11124))

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Abstract

SNOW 2.0 is a software-oriented stream cipher and internationally standardized by ISO/IEC 18033-4. In this paper, we present three attacks on SNOW 2.0 by MILP-aided automatic search algorithms. First, we present an efficient algorithm to find linear masks with the high correlation. It enables us to improve time and data complexities of the known fast correlation attacks. Then we propose a 17-round integral distinguisher out of 32 rounds by evaluating the propagation of the division property. Moreover, we propose a cube attack on the 14-round SNOW 2.0. The time complexity is \(2^{61.59}\) where \(2^{39}\) chosen IVs are required. As far as we know, these are the first investigations about integral and cube attacks of SNOW 2.0, respectively.

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Acknowledgment

This work was supported by JSPS KAKENHI Grant Numbers JP17K00184, JP17K12698.

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Authors and Affiliations

  1. Kobe University, 1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo, 657-8501, Japan

    Yuki Funabiki & Masakatu Morii

  2. NTT Secure Platform Laboratories, 3-9-11 Midori-cho, Musashino, Tokyo, 180-8585, Japan

    Yosuke Todo

  3. University of Hyogo, 7-1-28 Minatojima-minamimachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan

    Takanori Isobe

Authors
  1. Yuki Funabiki
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  2. Yosuke Todo
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  3. Takanori Isobe
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  4. Masakatu Morii
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Corresponding author

Correspondence to Yuki Funabiki .

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Editors and Affiliations

  1. IBM Research - Zurich, Rüschlikon, Switzerland

    Jan Camenisch

  2. KTH Royal Institute of Technology, Stockholm, Sweden

    Panos Papadimitratos

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Funabiki, Y., Todo, Y., Isobe, T., Morii, M. (2018). Several MILP-Aided Attacks Against SNOW 2.0. In: Camenisch, J., Papadimitratos, P. (eds) Cryptology and Network Security. CANS 2018. Lecture Notes in Computer Science(), vol 11124. Springer, Cham. https://doi.org/10.1007/978-3-030-00434-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-00434-7_20

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