Compact word-serial modular multiplier accelerator structure for cryptographic processors in IoT edge nodes with limited resources
Date
2022
Authors
Ibrahim, Atef
Gebali, Fayez
Journal Title
Journal ISSN
Volume Title
Publisher
Mathematics
Abstract
IoT is extensively used in many infrastructure applications, including telehealth, smart
homes, smart grids, and smart cities. However, IoT has the weakest link in system security since it
often has low processing and power resources. It is important to implement the necessary cryptographic
primitives in these devices using extremely efficient finite field hardware structures. Modular
multiplication is the core of cryptographic operators. Therefore, we present, in this work, a wordserial
modular multiplier accelerator structure that provides the system designer with the ability
to manage areas, delays, and energy consumption through selecting the appropriate embedded
processor word size l. The modularity and regularity of the suggested multiplier structure makes it
more suitable for implementation in ASIC technology. The ASIC implementation results indicates
that the offered multiplier structure achieves area reduction compared to the competitive existing
multiplier structures that vary from 76.2% to 98.5% for l = 8, from 73.1% to 98.1% for l = 16, and
from 82.9% to 98.3% for l = 32. Moreover, the energy reduction varies from 61.2% to 98.8% for l = 8,
from 67.7% to 98.3% for l = 16, and from 76.1% to 98.8% for l = 32. These results indicate that
the proposed modular multiplier structure significantly outperforms the competitive ones, in terms
of area and consumed energy, making it more suitable for utilization in resource-constrained IoT
edge devices.
Description
Keywords
modular multipliers, embedded security, IoT network, hardware security, parallel computing, cryptography
Citation
Ibrahim, A. & Gebali, F. (2022). “Compact word-serial modular multiplier accelerator structure for cryptographic processors in IoT edge nodes with limited resources.” Mathematics, 10(5), 848. https://doi.org/10.3390/math10050848