Improving BDD Enumeration for LWE Problem Using GPU

Autor: Mohamed S. Esseissah, Ashraf Bhery, Hatem M. Bahig

Publikováno v: IEEE Access, Vol 8, Pp 19737-19749 (2020)

In this paper, we present a GPU-based parallel algorithm for the Learning With Errors (LWE) problem using a lattice-based Bounded Distance Decoding (BDD) approach. To the best of our knowledge, this is the first GPU-based implementation for the LWE p

Externí odkaz: https://doaj.org/article/2db4648b4da8450498db369e00274f6d

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Improved Hardness of BDD and SVP Under Gap-(S)ETH

Autor: Bennett, Huck, Peikert, Chris, Tang, Yi

We show improved fine-grained hardness of two key lattice problems in the ����_p norm: Bounded Distance Decoding to within an �� factor of the minimum distance (BDD_{p, ��}) and the (decisional) ��-approximate Shortest Vector Prob

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00034c8c84aaa7d39d1a82f26f6cb7f6

Improved (Provable) Algorithms for the Shortest Vector Problem via Bounded Distance Decoding

Autor: Aggarwal, Divesh, Chen, Yanlin, Kumar, Rajendra, Shen, Yixin

Publikováno v: The 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021)
The 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021), Mar 2021, Saarbrücken, Germany. ⟨10.4230/LIPIcs.STACS.2021.4⟩

The most important computational problem on lattices is the Shortest Vector Problem (SVP). In this paper, we present new algorithms that improve the state-of-the-art for provable classical/quantum algorithms for SVP. We present the following results.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60f88e765207a14568e0923225d1711d
https://hal.archives-ouvertes.fr/hal-03363367/document