Highly-Efficient Hardware Architecture for ML-KEM PQC Standard

The advent of quantum computers, with their immense computational potential, poses significant threats to traditional cryptographic systems. In response, NIST announced the quantum-resistant Module Lattice-based Key Encapsulation Mechanism (ML-KEM) standard in 2024. This paper presents an efficient hardware architecture for the ML-KEM scheme, capable of supporting all algorithms and flexibly adapting to different security levels. The proposed design achieves a balance between high performance and low hardware resource consumption, making it suitable for deployment across various FPGA platforms. Key innovations include the Unified Polynomial Arithmetic Module (UniPAM), capable of handling all polynomial arithmetic operations, and an optimized hash module for the SHA-3 variants integral to ML-KEM. Additionally, the design introduces an efficient timing diagram and conflict-free memory management strategy, enabling seamless parallelism and reducing execution time while minimizing hardware resource consumption. Furthermore, the implementation incorporates several methods to effectively mitigate side-channel attacks, a common concern in hardware-based cryptosystem deployments. The proposed architecture is validated through implementation on an Artix-7 FPGA and Synopsys 14nm ASIC technology. Compared to state-of-the-art designs, our approach demonstrates superior performance while maintaining comparable hardware resource efficiency. Specifically, the hardware implementation on the Xilinx Artix-7 utilizes 12k LUTs, 6.9k FFs, 4 DSPs, and 9 BRAMs at clock frequency of 220 MHz.

Authors

Institutions

Publication Details

Journal
IEEE Open Journal of Circuits and Systems
Published
2025-01-01
DOI
https://doi.org/10.1109/ojcas.2025.3591136
Citations
3
Primary Topic
Metallurgy and Material Forming
Type
article
Field-Weighted Citation Impact
2.59

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Highly-Efficient Hardware Architecture for ML-KEM PQC Standard

Haesung Jung, Quang Truong, Hanho Lee
3 citations
IEEE Open Journal of Circuits and Systems
Metallurgy and Material Forming
2.59
article

Highly-Efficient Hardware Architecture for ML-KEM PQC Standard

Haesung Jung, Quang Truong, Hanho Lee
article en
3 citations

Abstract

The advent of quantum computers, with their immense computational potential, poses significant threats to traditional cryptographic systems. In response, NIST announced the quantum-resistant Module Lattice-based Key Encapsulation Mechanism (ML-KEM) standard in 2024. This paper presents an efficient hardware architecture for the ML-KEM scheme, capable of supporting all algorithms and flexibly adapting to different security levels. The proposed design achieves a balance between high performance and low hardware resource consumption, making it suitable for deployment across various FPGA platforms. Key innovations include the Unified Polynomial Arithmetic Module (UniPAM), capable of handling all polynomial arithmetic operations, and an optimized hash module for the SHA-3 variants integral to ML-KEM. Additionally, the design introduces an efficient timing diagram and conflict-free memory management strategy, enabling seamless parallelism and reducing execution time while minimizing hardware resource consumption. Furthermore, the implementation incorporates several methods to effectively mitigate side-channel attacks, a common concern in hardware-based cryptosystem deployments. The proposed architecture is validated through implementation on an Artix-7 FPGA and Synopsys 14nm ASIC technology. Compared to state-of-the-art designs, our approach demonstrates superior performance while maintaining comparable hardware resource efficiency. Specifically, the hardware implementation on the Xilinx Artix-7 utilizes 12k LUTs, 6.9k FFs, 4 DSPs, and 9 BRAMs at clock frequency of 220 MHz.

IEEE Open Journal of Circuits and SystemsVol. 6
Inha University (KR)
Ministry of Science and ICT, South Korea
Affordable and clean energy
Openalex Percentile: Top 10%
Metallurgy and Material Forming
2.59
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Highly-Efficient Hardware Architecture for ML-KEM PQC Standard — Haesung Jung, Quang Truong, et al. · IEEE Open Journal of Circuits and Systems (2025) | TGRS Research Map | TGRS