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DOI: 10.14569/IJACSA.2024.0151092
PDF

Balancing Privacy and Performance: Exploring Encryption and Quantization in Content-Based Image Retrieval Systems

Author 1: Mohamed Jafar Sadik
Author 2: Noor Azah Samsudin
Author 3: Ezak Fadzrin Bin Ahmad

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 10, 2024.

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Abstract: This paper presents three significant contributions to the field of privacy-preserving Content-Based Image Retrieval (CBIR) systems for medical imaging. First, we introduce a novel framework that integrates VGG-16 Convolutional Neural Network with a multi-tiered encryption scheme specifically designed for medical image security. Second, we propose an innovative approach to model optimization through three distinct quantization methods (max, 99% percentile, and KL divergence), which significantly reduces computational overhead while maintaining retrieval accuracy. Third, we provide comprehensive empirical evidence demonstrating the framework's effectiveness across multiple medical imaging modalities, achieving 94.6% accuracy with 99% percentile quantization while maintaining privacy through encryption. Our experimental results, conducted on a dataset of 1,200 medical images across three anatomical categories (lung, brain, and bone), show that our approach successfully balances the competing demands of privacy preservation, computational efficiency, and retrieval accuracy. This work represents a significant advancement in making secure CBIR systems practically deployable in resource-constrained healthcare environments.

Keywords: Content-Based Image Retrieval (CBIR); Convolutional Neural Networks (CNN): Encrypted data; Feature extraction; Fully Homomorphic Encryption (FHE); medical imaging; privacy; quantization; retrieval accuracy

Mohamed Jafar Sadik, Noor Azah Samsudin and Ezak Fadzrin Bin Ahmad, “Balancing Privacy and Performance: Exploring Encryption and Quantization in Content-Based Image Retrieval Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 15(10), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151092

@article{Sadik2024,
title = {Balancing Privacy and Performance: Exploring Encryption and Quantization in Content-Based Image Retrieval Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151092},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151092},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {10},
author = {Mohamed Jafar Sadik and Noor Azah Samsudin and Ezak Fadzrin Bin Ahmad}
}



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.

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