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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.

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1009240
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Title
Efficient Fine-Grained LuT-Based Optimization of AES MixColumns and InvMixColumns for FPGA Implementation
Author
Azzouzi Oussama 1   VIAFID ORCID Logo  ; Anane, Mohamed 2   VIAFID ORCID Logo  ; Ghanem Mohamed Chahine 3   VIAFID ORCID Logo  ; Himeur Yassine 4   VIAFID ORCID Logo  ; Hamza, Kheddar 5   VIAFID ORCID Logo 

 Department of Computer Science, Centre Universitaire El Cherif Bouchoucha Aflou, Aflou 03001, Algeria; [email protected], Laboratory of System Design Methods, National Higher School of Computer Science, BP 68M, Algiers 16309, Algeria; [email protected] 
 Laboratory of System Design Methods, National Higher School of Computer Science, BP 68M, Algiers 16309, Algeria; [email protected] 
 Cybersecuirty Institute, University of Liverpool, Liverpool L69 3BX, UK, Cyber Secuirty Research Centre, London Metropolitan University, London N7 8DB, UK; [email protected] 
 College of Engineering and Information Technology, University of Dubai, Dubai 14143, United Arab Emirates; [email protected] 
 Cyber Secuirty Research Centre, London Metropolitan University, London N7 8DB, UK; [email protected], Laboratoire des Systèmes Électroniques Avancés, Department of Electrical Engineering, University of Medea, Medea 26000, Algeria 
Publication title
Volume
14
Issue
24
First page
4912
Number of pages
16
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
e-ISSN
20799292
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-12-14
Milestone dates
2025-11-13 (Received); 2025-12-12 (Accepted)
Publication history
 
 
   First posting date
14 Dec 2025
ProQuest document ID
3286275975
Document URL
https://www.proquest.com/scholarly-journals/efficient-fine-grained-lut-based-optimization-aes/docview/3286275975/se-2?accountid=208611
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-24
Database
ProQuest One Academic