AXMM: Area and power efficient approximate modular multiplier for R-LWE cryptosystem

Dur E. Shahwar Kundi*, Song Bian, Ayesha Khalid, Chenghua Wang, Máire O'Neill, Weiqiang Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Amongst various Post-Quantum Cryptographic (PQC) schemes, Lattice-Based Cryptography (LBC) stands out as the most viable substitute to the classical cryptographic schemes due to its efficiency, versatility and solid foundations on hard mathematical problems. Ring Learning With Errors (R-LWE) is a Public Key Encryption (PKE) scheme of LBC, in which the modular polynomial multiplication in a ring is the main bottleneck in the realization of a practical resource-constraint design for the embedded IoT devices. This work explores novel Approximate Computing (AC) technique for the design of area/power efficient modular multiplier (so called AxMM) for R-LWE, exploiting the inherent approximate structure of the scheme. The proposed AxMM on 45nm ASIC library achieved an area and power reduction of 36% and 23%, respectively, along with a speed increase of 1.34× as compared to state-of-art smallest exact R-LWE modular multiplier.

Original languageEnglish
Title of host publication2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728133201
DOIs
Publication statusPublished - 28 Sep 2020
Event52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual, Online
Duration: 10 Oct 202021 Oct 2020

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2020-October
ISSN (Print)0271-4310

Conference

Conference52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
CityVirtual, Online
Period10/10/202021/10/2020

Bibliographical note

Funding Information:
*The authors gratefully acknowledge the support of K.C.Wong Education Foundation.

Publisher Copyright:
© 2020 IEEE

Keywords

  • Approximate computing (AC)
  • Lattice-based cryptography (LBC)
  • Ring-learning with errors (R-LWE)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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