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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 5, 2025.
Abstract: One new area of secure computing and privacy is homomorphic encryption (HE). An FPGA-based implementation of the HE algorithm, Enhanced DGHV, which helps real-time computation on encrypted text without disclosing the original data, is developed in this study. This research aims to focus on implementing the Enhanced DGHV Fully HE algorithm on FPGA hardware to achieve a more efficient scheme in terms of performance and security. The Xilinx Vivado tool implements the design on a Genesys 2 Kintex 7 FPGA board. While software simulation with 3.2% I/O usage, the simulation confirms a total power consumption of 3.12W (watts), highlighting successful synthesis with little resources. At 9.105W, the hardware implementation is comparable. Furthermore, an effective FPGA-based implementation confirms a method for achieving a balance between power consumption and performance while implementing the DGHV algorithm. The results show that the overall computational complexity can be reduced, and the hardware and software integration help to achieve an increased data security level for homomorphic encryption algorithms with improved efficiency.
Gurdeep Singh, Sonam Mittal, Hani Moaiteq Aljahdali, Ahmed Hamza Osman, Ala Eldin A Awouda, Ashraf Osman Ibrahim and Salil Bharany, “FPGA-Based Implementation of Enhanced DGHV Homomorphic Encryption: A Power-Efficient Approach to Secure Computing” International Journal of Advanced Computer Science and Applications(IJACSA), 16(5), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160540
@article{Singh2025,
title = {FPGA-Based Implementation of Enhanced DGHV Homomorphic Encryption: A Power-Efficient Approach to Secure Computing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160540},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160540},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {5},
author = {Gurdeep Singh and Sonam Mittal and Hani Moaiteq Aljahdali and Ahmed Hamza Osman and Ala Eldin A Awouda and Ashraf Osman Ibrahim and Salil Bharany}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.