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March 6, 2026International Journal of Internet Manufacturing and Services

A Hybrid Huffman-CNN-AES Deep Learning Framework for Secure Medical Image Steganography: H-CADStego

RAMAPRIYA B Y. Kalpana

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Key Points

The aim is to develop a secure framework for embedding information in medical images using deep learning techniques.
Utilized a hybrid model combining Huffman coding, Convolutional Neural Network (CNN), and Advanced Encryption Standard (AES).
Focused on medical image data for steganography.
Implemented deep learning approaches for enhanced image security.
Achieved higher security levels by integrating three advanced techniques.
Demonstrated effectiveness in secure data embedding within medical images.
Showed improved performance metrics in steganographic applications.

Implication

Demonstrates a novel deep learning framework for secure steganography in medical images, suggesting enhanced data protection.

Abstract

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Cite This Study

B et al. (2026) studied this question.

synapsesocial.com/papers/69ada836bc08abd80d5bb49a https://doi.org/10.1504/ijims.2028.10076831

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