Efficient Fine-Grained LuT-Based Optimization of AES MixColumns and InvMixColumns for FPGA Implementation

This paper presents fine-grained Field Programmable Gate Arrays (FPGA) architectures for the Advanced Encryption Standard (AES) MixColumns and InvMixColumns transformations, targeting improved performance and resource utilization. The proposed method reformulates these operations as boolean functions directly mapped onto FPGA Lookup-Table (LuT) primitives, replacing conventional xor-based arithmetic with memory-level computation. A custom MATLAB-R2019a-based pre-synthesis optimization algorithm performs algebraic simplification and shared subexpression extraction at the polynomial level of Galois Field GF(28), reducing redundant logic memory. This architecture, LuT-level optimization minimizes the delay of the complex InvMixColumns stage and narrows the delay gap between encryption (1.305 ns) and decryption (1.854 ns), resulting in a more balanced and power-efficient AES pipeline. Hardware implementation on a Xilinx Virtex-5 FPGA confirms the efficiency of the design, demonstrating competitive performance compared to state-of-the-art FPGA realizations. Its fast performance and minimal hardware requirements make it well suited for real-time secure communication systems and embedded platforms with limited resources that need reliable bidirectional data processing.

Authors

Institutions

Publication Details

Journal
Electronics
Published
2025-12-14
DOI
https://doi.org/10.3390/electronics14244912
Primary Topic
Cryptographic Implementations and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient Fine-Grained LuT-Based Optimization of AES MixColumns and InvMixColumns for FPGA Implementation

Yassine Himeur, Oussama Azzouzi, Hamza Kheddar, Mohamed Chahine Ghanem et al.
Electronics
Cryptographic Implementations and Security
article

Efficient Fine-Grained LuT-Based Optimization of AES MixColumns and InvMixColumns for FPGA Implementation

Yassine Himeur, Oussama Azzouzi, Hamza Kheddar, Mohamed Chahine Ghanem, Mohamed Anane
article en

Abstract

This paper presents fine-grained Field Programmable Gate Arrays (FPGA) architectures for the Advanced Encryption Standard (AES) MixColumns and InvMixColumns transformations, targeting improved performance and resource utilization. The proposed method reformulates these operations as boolean functions directly mapped onto FPGA Lookup-Table (LuT) primitives, replacing conventional xor-based arithmetic with memory-level computation. A custom MATLAB-R2019a-based pre-synthesis optimization algorithm performs algebraic simplification and shared subexpression extraction at the polynomial level of Galois Field GF(28), reducing redundant logic memory. This architecture, LuT-level optimization minimizes the delay of the complex InvMixColumns stage and narrows the delay gap between encryption (1.305 ns) and decryption (1.854 ns), resulting in a more balanced and power-efficient AES pipeline. Hardware implementation on a Xilinx Virtex-5 FPGA confirms the efficiency of the design, demonstrating competitive performance compared to state-of-the-art FPGA realizations. Its fast performance and minimal hardware requirements make it well suited for real-time secure communication systems and embedded platforms with limited resources that need reliable bidirectional data processing.

ElectronicsVol. 14(24)
London Metropolitan University (GB), University of Dubai (AE), University of Liverpool (GB), Higher National Veterinary School (DZ), National Higher School of Statistics and Applied Economy (DZ), University Yahia Fares of Medea (DZ), Centre Universitaire de Mila (DZ)
Openalex Percentile: Top 79%
Cryptographic Implementations and Security
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.