Paper 2020/054
Parameterized Hardware Accelerators for Lattice-Based Cryptography and Their Application to the HW/SW Co-Design of qTESLA
Wen Wang and Shanquan Tian and Bernhard Jungk and Nina Bindel and Patrick Longa and Jakub Szefer
Abstract
This paper presents a set of efficient and parameterized hardware accelerators that target post-quantum lattice-based cryptographic schemes, including a versatile cSHAKE core, a binary-search CDT-based Gaussian sampler, and a pipelined NTT-based polynomial multiplier, among others. Unlike much of prior work, the accelerators are fully open-sourced, are designed to be constant-time, and are parameterized at compile-time to support different parameters without the need for re-writing the hardware implementation. These flexible, to-be publicly-available accelerators are used to demonstrate the first hardware-software co-design using RISC-V of the post-quantum lattice-based signature scheme qTESLA with provably secure parameters. In particular, we demonstrate that the NIST's Round 2 level 1 and level 3 qTESLA variants achieve over a 40-100x speedup for key generation, about a 10x speedup for signing, and about a 16x speedup for verification, compared to the baseline RISC-V software-only implementation. For instance, this corresponds to execution in 7.7, 34.4, and 7.8 milliseconds for key generation, signing, and verification, respectively, for qTESLA's level 1 parameter set on an Artix-7 FPGA, demonstrating the feasibility of the scheme for embedded applications.
Metadata
- Available format(s)
- Category
- Implementation
- Publication info
- Preprint. MINOR revision.
- Keywords
- Lattice-based cryptographyPost-quantum cryptographyqTESLAHardware acceleratorsHardware-software co-designFPGARISC-V
- Contact author(s)
- wen wang ww349 @ yale edu,shanquan tian @ yale edu,jakub szefer @ yale edu,bernhard @ projectstarfire de,nlbindel @ uwaterloo ca,plonga @ microsoft com
- History
- 2020-04-11: revised
- 2020-01-20: received
- See all versions
- Short URL
- https://ia.cr/2020/054
- License
-
CC BY