Unknown

Dataset Information

0

Sieve, Enumerate, Slice, and Lift: Hybrid Lattice Algorithms for SVP via CVPP


ABSTRACT: Motivated by recent results on solving large batches of closest vector problem (CVP) instances, we study how these techniques can be combined with lattice enumeration to obtain faster methods for solving the shortest vector problem (SVP) on high-dimensional lattices. Theoretically, under common heuristic assumptions we show how to solve SVP in dimension d with a cost proportional to running a sieve in dimension Practically, the main obstacles for observing a speedup in moderate dimensions appear to be that the leading constant in the

SUBMITTER: Nitaj A 

PROVIDER: S-EPMC7335001 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC9945929 | biostudies-literature
| S-EPMC7598097 | biostudies-literature
| S-EPMC8319201 | biostudies-literature
| S-EPMC6403309 | biostudies-literature
| S-EPMC4889378 | biostudies-literature
| S-EPMC5727779 | biostudies-literature
| S-EPMC9263155 | biostudies-literature
| S-EPMC6193992 | biostudies-literature
| S-EPMC10431705 | biostudies-literature
| S-EPMC7788080 | biostudies-literature