Improved Plantard Arithmetic for Lattice-based Cryptography

Junhao Huang, Jipeng Zhang, Haosong Zhao, Zhe Liu, Ray C. C. Cheung, Çetin Kaya Koç, Donglong Chen*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

46 Citations (Scopus)
744 Downloads (CityUHK Scholars)

Abstract

This paper presents an improved Plantard’s modular arithmetic (Plantard arithmetic) tailored for Lattice-Based Cryptography (LBC). Based on the improved Plantard arithmetic, we present faster implementations of two LBC schemes, Kyber and NTTRU, running on Cortex-M4. The intrinsic advantage of Plantard arithmetic is that one multiplication can be saved from the modular multiplication of a constant. However, the original Plantard arithmetic is not very practical in LBC schemes because of the limitation on the unsigned input range. In this paper, we improve the Plantard arithmetic and customize it for the existing LBC schemes with theoretical proof. The improved Plantard arithmetic not only inherits its aforementioned advantage but also accepts signed inputs, produces signed output, and enlarges its input range compared with the original design. Moreover, compared with the state-of-the-art Montgomery arithmetic, the improved Plantard arithmetic has a larger input range and smaller output range, which allows better lazy reduction strategies during the NTT/INTT implementation in current LBC schemes. All these merits make it possible to replace the Montgomery arithmetic with the improved Plantard arithmetic in LBC schemes on some platforms. After applying this novel method to Kyber and NTTRU schemes using 16-bit NTT on Cortex-M4 devices, we show that the proposed design outperforms the known fastest implementation that uses Montgomery and Barrett arithmetic. Specifically, compared with the state-of-the-art Kyber implementation, applying the improved Plantard arithmetic in Kyber results in a speedup of 25.02% and 18.56% for NTT and INTT, respectively. Compared with the reference implementation of NTTRU, our NTT and INTT achieve speedup by 83.21% and 78.64%, respectively. As for the LBC KEM schemes, we set new speed records for Kyber and NTTRU running on Cortex-M4.
Original languageEnglish
Pages (from-to)614-636
JournalIACR Transactions on Cryptographic Hardware and Embedded Systems
Volume2022
Issue number4
Online published31 Aug 2022
DOIs
Publication statusPublished - 2022

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Funding

The authors would like to thank the anonymous reviewers (including the shepherd: BoYin Yang) and Hao Cheng for their constructive suggestions and comments on our paper. This work is partially supported by the National Key R&D Program of China (No.2020AAA0107703 and No.2021YFB3100700), the National Natural Science Foundation of China (No. 62002023 and No.62132008), the Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College (2022B1212010006), Guangdong Higher Education Upgrading Plan (2021-2025) (UIC R0400001-22), Guangdong Higher Education Key Platform and Research Project (No. 2020KQNCX100), Hong Kong Innovation and Technology Commission (InnoHK Project CIMDA), and Hong Kong Research Grants Council (Project 11204821)

Research Keywords

  • Cortex-M4
  • Kyber
  • lattice-based cryptography
  • modular arithmetic
  • NTT
  • NTTRU

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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