Work

Benchmarking NIST LWC candidates over GF22FDx achieving 3.5 Tb/J and 4.4 Gbps for IoT applications

Year: 2025

Type: article

Abstract: Cryptography is a cornerstone of Internet-of-Things (IoT) security, protecting sensitive data and ensuring the integrity of communication channels. Standard cryptography, designed for server environments with ample resources algorithms e.g. Advanced Encryption Standard (AES), may not be suitable for the resource-constrained devices prevalent in IoT nodes, edge computing, and Unmanned Aerial Vehicles (UAVs). National Institute of Standards and Technology (NIST) initiated a standardization process for Lightweight Cryptography (LWC) algorithms to address this challenge. Ten candidate algorithms were selected for the final round in 2021, and Ascon was announced as the recommended LWC in 2023 and then published as a Special Publication (SP 800-232) instead of a Federal Information Processing Standard (FIPS) standard. As an SP, the use of Ascon in IoT nodes is recommended but not mandatory. This flexibility allows for the consideration of alternative algorithms based on specific application needs of area, performance and/or energy efficiency. Therefore, it is essential to evaluate and rank other LWC candidates in each metric. In addition, exploring Hardware (HW), Software (SW), and HW/SW co-design architectures is vital in IoT to meet diverse security and computational needs. This work provides a complete silicon-based benchmarking for the final candidates using three different architectures of HW, SW and HW/SW. Benchmarking is conducted fairly by unifying architectures, optimizations, and fabrication over the same chip. CMOS Global Foundries (GF22FDx) technology is used for fabrication. Results show that HW enhances the throughput by up to 6 orders of magnitude and energy efficiency by up to 5 orders of magnitude compared to SW. Xoodyak stands out as a top performer in terms of energy efficiency, while Sparkle excels in throughput, and TinyJambu is the smallest in terms of area.

Source: Computers & Electrical Engineering

DOI: 10.1016/j.compeleceng.2025.110758