Learnable Markov Chain Monte Carlo Sampling Methods for Lattice Gaussian Distribution

Autor: Zheng Wang, Shanxiang Lyu, Ling Liu

Publikováno v: IEEE Access, Vol 7, Pp 87494-87503 (2019)

As a key ingredient of machine learning and artificial intelligence, the sampling algorithms with respect to lattice Gaussian distribution has emerged as an important problem in coding and decoding of wireless communications. In this paper, based on

Externí odkaz: https://doaj.org/article/6077a52538154ced9c5b3d2df7fc8536

Key Recovery from Gram-Schmidt Norm Leakage in Hash-and-Sign Signatures over NTRU Lattices

Autor: Paul Kirchner, Mehdi Tibouchi, Alexandre Wallet, Pierre-Alain Fouque, Yang Yu

Publikováno v: Advances in Cryptology – EUROCRYPT 2020
Advances in Cryptology – EUROCRYPT 2020, May 2020, Zagreb, Croatia. pp.34-63, ⟨10.1007/978-3-030-45727-3_2⟩
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Advances in Cryptology – EUROCRYPT 2020
Advances in Cryptology – EUROCRYPT 2020 ISBN: 9783030457266
EUROCRYPT (3)
Advances in Cryptology – EUROCRYPT 2020-39th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Zagreb, Croatia, May 10–14, 2020, Proceedings, Part III

International audience; In this paper, we initiate the study of side-channel leakage in hash-and-sign lattice-based signatures, with particular emphasis on the two efficient implementations of the original GPV lattice-trapdoor paradigm for signatures

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fda5ca4745d8c30067d4ce82820a3b5d
https://inria.hal.science/hal-03854922

On the geometric ergodicity of Gibbs algorithm for lattice Gaussian sampling

Autor: Cong Ling, Zheng Wang

Publikováno v: ITW
2017 IEEE Information Theory Workshop (ITW)

Sampling from the lattice Gaussian distribution is emerging as an important problem in coding and cryptography. In this paper, the conventional Gibbs sampling algorithm is demonstrated to be geometrically ergodic in tackling with lattice Gaussian sam

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::86c354a2b4794a32f789507cb3d5f3cf
https://doi.org/10.1109/itw.2017.8278001

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