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Preimage Sampling in the Higher-bit Approximate Setting with a Non-spherical Gaussian Sampler

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Information Security and Cryptology – ICISC 2022 (ICISC 2022)

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Abstract

Approximate lattice trapdoors are introduced to improve the efficiency of lattice-based hash-and-sign signature. There are two improvements of the approximate setting for such schemes. The first is to use a non-spherical Gaussian sampler, and the second is the higher-bit approximate setting.

In this paper we consider further improvements of the approximate setting, namely we combine the higher-bit approximate setting with the use of a non-spherical Gaussian sampler. We assess the effectiveness of this approach by doing an analysis with a proof-of-concept implementation. We observe that our construction brings several improvements, especially in the public key size and signature size. Moreover, an exhaustive search for parameter sets make us aware of new parameters choices which lead to better results in the higher-bit approximate setting than those of previous work.

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Acknowledgement

This work has benefited from state aid managed by the National Research Agency under the France 2030 Plan bearing the reference ANR-22-PETQ-0006.

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Authors and Affiliations

  1. Inria & Laboratoire CNRS LIX, École Polytechnique, Institut Polytechnique de Paris, Palaiseau, France

    Anaëlle Le Dévéhat

  2. Graduate School of Information Sciences, Tohoku University, Sendai, Japan

    Shingo Hasegawa & Hiroki Shizuya

Authors
  1. Anaëlle Le Dévéhat
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  2. Shingo Hasegawa
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  3. Hiroki Shizuya
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Corresponding author

Correspondence to Shingo Hasegawa .

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Editors and Affiliations

  1. Hanyang University, Ansan, Korea (Republic of)

    Seung-Hyun Seo

  2. Hansung University, Seoul, Korea (Republic of)

    Hwajeong Seo

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Dévéhat, A.L., Hasegawa, S., Shizuya, H. (2023). Preimage Sampling in the Higher-bit Approximate Setting with a Non-spherical Gaussian Sampler. In: Seo, SH., Seo, H. (eds) Information Security and Cryptology – ICISC 2022. ICISC 2022. Lecture Notes in Computer Science, vol 13849. Springer, Cham. https://doi.org/10.1007/978-3-031-29371-9_23

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  • DOI: https://doi.org/10.1007/978-3-031-29371-9_23

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  • Print ISBN: 978-3-031-29370-2

  • Online ISBN: 978-3-031-29371-9

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