Parameterized hardware accelerators for lattice-based cryptography and their application to the hw/sw co-design of qtesla

Wen Wang, Shanquan Tian, Bernhard Jungk, Nina Bindel, Patrick Longa, Jakub Szefer

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

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 can be parameterized at compile-time to support different parameters without the need for re-writing the hardware implementation. These flexible, publicly-available accelerators are leveraged 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, this work demonstrates 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.

Original languageEnglish (US)
Pages (from-to)269-306
Number of pages38
JournalIACR Transactions on Cryptographic Hardware and Embedded Systems
Volume2020
Issue number3
DOIs
StatePublished - 2020

Keywords

  • FPGA
  • Hardware accelerators
  • Hardware-software co-design
  • Lattice-based cryptography
  • Post-quantum cryptography
  • QTESLA
  • RISC-V

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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