Machine Learning for Reversible Data Hiding in Plaintext or Cipher Text Multimedia
Laaouina Najwa · International Journal of Research and Innovation in Social Science · 2025
Reversible Data Hiding (RDH) approaches embed secret information into digital multimedia content, allowing the original content to be fully restored once the concealed data is retrieved. This study investigates the integration of Machine Learning (ML) techniques with RDH, focusing on plaintext and cipher text multimedia. The study employs machine learning models, such as neural networks, to improve embedding efficiency and robustness, optimizing data embedding and extraction operations while preserving the integrity of the host media. The proposed methods outperform existing RDH techniques in terms of embedding capacity, data security, and image quality.