Paper 2017/1228
Speed-ups and time-memory trade-offs for tuple lattice sieving
Gottfried Herold, Elena Kirshanova, and Thijs Laarhoven
Abstract
In this work we study speed-ups and time-space trade-offs for solving the shortest vector problem (SVP) on Euclidean lattices based on tuple lattice sieving.
Our results extend and improve upon previous work of Bai-Laarhoven-Stehlë [ANTS'16] and Herold-Kirshanova [PKC'17], with better complexities for arbitrary tuple sizes and offering tunable time-memory trade-offs.The trade-offs we obtain stem from the generalization and combination of two algorithmic techniques: the configuration framework introduced by Herold-Kirshanova, and the spherical locality-sensitive filters of Becker-Ducas-Gama-Laarhoven [SODA'16].
When the available memory scales quasi-linearly with the list size, we show that with triple sieving we can solve SVP in dimension
Note: Fixed a typo in the title
Metadata
- Available format(s)
-
PDF
- Publication info
- A major revision of an IACR publication in PKC 2018
- Keywords
- lattice-based cryptographyshortest vector problem (SVP)nearest neighbor algorithmslattice sieving
- Contact author(s)
- elena kirshanova @ ens-lyon fr
- History
- 2017-12-22: revised
- 2017-12-22: received
- See all versions
- Short URL
- https://ia.cr/2017/1228
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2017/1228, author = {Gottfried Herold and Elena Kirshanova and Thijs Laarhoven}, title = {Speed-ups and time-memory trade-offs for tuple lattice sieving}, howpublished = {Cryptology {ePrint} Archive, Paper 2017/1228}, year = {2017}, url = {https://eprint.iacr.org/2017/1228} }