[Resource Topic] 2019/1009: LLL and stochastic sandpile models

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LLL and stochastic sandpile models

Authors: Jintai Ding, Seungki Kim, Tsuyoshi Takagi, Yuntao Wang


We introduce stochastic sandpile models which imitate numerous aspects of the practical behavior of the LLL algorithm with compelling accuracy. In addition, we argue that the physics and mathematics of sandpile models provide satisfactory heuristic explanations to much of the mysteries of LLL, and pleasant implications for lattice-based cryptography as a whole. Based on these successes, we suggest a paradigm in which one regards blockwise reduction algorithms as 1-d stochastic self-organized criticality(SOC) models and study them as such.

ePrint: https://eprint.iacr.org/2019/1009

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