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Exploiting the Symmetry of $\mathbb{Z}^n$: Randomization and the Automorphism Problem
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Conference:  ASIACRYPT 2023 
Abstract:  $\mathbb{Z}^n$ is one of the simplest types of lattices, but the computational problems on its rotations, such as $\mathbb{Z}$SVP and $\mathbb{Z}$LIP, have been of great interest in cryptography. Recent advances have been made in building cryptographic primitives based on these problems, as well as in developing new algorithms for solving them. However, the theoretical complexity of $\mathbb{Z}$SVP and $\mathbb{Z}$LIP are still not well understood. In this work, we study the problems on rotations of $\mathbb{Z}^n$ by exploiting the symmetry property. We introduce a randomization framework that can be roughly viewed as `applying random automorphismsâ€™ to the output of an oracle, without accessing the automorphism group. Using this framework, we obtain new reduction results for rotations of $\mathbb{Z}^n$. First, we present a reduction from $\mathbb{Z}$LIP to $\mathbb{Z}$SCVP. Here $\mathbb{Z}$SCVP is the problem of finding the shortest characteristic vectors, which is a special case of CVP where the target vector is a deep hole of the lattice. Moreover, we prove a reduction from $\mathbb{Z}$SVP to $\gamma$$\mathbb{Z}$SVP for any constant $\gamma = O(1)$ in the same dimension, which implies that $\mathbb{Z}$SVP is as hard as its approximate version for any constant approximation factor. Second, we investigate the problem of finding a nontrivial automorphism for a given lattice, which is called LAP. Specifically, we use the randomization framework to show that $\mathbb{Z}$LAP is as hard as $\mathbb{Z}$LIP. We note that our result can be viewed as a $\mathbb{Z}^n$analogue of Lenstra and Silverberg's result in [JoC2017], but with a different assumption: they assume the $G$lattice structure, while we assume the access to an oracle that outputs a nontrivial automorphism. 
BibTeX
@inproceedings{asiacrypt202333380, title={Exploiting the Symmetry of $\mathbb{Z}^n$: Randomization and the Automorphism Problem}, publisher={SpringerVerlag}, author={Kaijie Jiang and Anyu Wang and Hengyi Luo and Guoxiao Liu and Yang Yu and Xiaoyun Wang}, year=2023 }