Marwa M. A. Hadhoud

Work place: Department of Biomedical Engineering, Faculty of Engineering, Capital University, Cairo, Helwan, Egypt

E-mail: marwa_hadhoud@h-eng.helwan.edu.eg

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Biography

Marwa M. A. Hadhoud is an Associate Professor at the Biomedical Engineering Department, College of Engineering, King Faisal University, Saudi Arabia, and also holds an associate professor position in the Biomedical Engineering Department, Faculty of Engineering, Capital University, Egypt. She received her BSc, MSc in biomedical engineering from faculty of Engineering Helwan University in 2003 and 2007 respectively. In 2012 she received a dual degree PhD in Biomedical Engineering from faculty of Engineering Helwan University and politecnico di Torino Italy. Her research interests are medical signal/image processing, pattern recognition, and Bioinformatics.

Author Articles
Secure and Efficient Image Encryption Scheme Based on Compressive Sensing and AES

By Shimaa Sayed Mohamed Marwa M. A. Hadhoud Fatty M. Salem

DOI: https://doi.org/10.5815/ijcnis.2026.05.03, Pub. Date: 8 Oct. 2026

Secure and efficient transmission of medical images requires integrating compression, encryption, and substitution mechanisms to protect sensitive patient data. Compression reduces image size, improving transmission and storage while preserving diagnostic quality. Encryption ensures confidentiality and the Health Insurance Portability and Accountability Act (HIPAA) compliance, safeguarding patient information from unauthorized access. Nonlinear substitution using dynamic S-boxes increases confusion and strengthens resistance to cryptanalysis. This paper presents a hybrid medical image encryption scheme comprising three sequential stages for high security and computational efficiency. In preprocessing, images are resized, normalized, partitioned into uniform blocks, and compressed using compressive sensing based on partial discrete Fourier transform sampling. The encryption stage applies adaptive S-boxes with block interleaving, followed by the Advanced Encryption Standard in Galois/Counter Mode to provide integrity-preserving encryption. During decryption, the Fast Iterative Shrinkage-Threshold Algorithm reconstructs images accurately. Experimental results demonstrate that the scheme preserves image quality, achieves effective compression, and resists statistical and cryptographic attacks, making it suitable for secure medical image communication in resource-limited environments.

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