What question did this study set out to answer?

To develop a high-capacity reversible data hiding method for encrypted images using most significant bit prediction to enhance data privacy in cloud environments.

January 29, 2018IEEE Transactions on Information Forensics and SecurityOpen Access

An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images

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Authors

PPPauline PuteauxCentre National de la Recherche Scientifique WPWilliam PuechLaboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier

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Overview

Algorithm evaluation demonstrates superior embedding capacity and image reconstruction quality in encrypted images, suggesting enhanced privacy protection for cloud storage.

Key Points

To develop a high-capacity reversible data hiding method for encrypted images using most significant bit prediction to enhance data privacy in cloud environments.
Designed an MSB prediction framework to embed auxiliary data into encrypted images without accessing the original image content or encryption key.
Formulated two implementation approaches: one using prediction error correction and another embedding prediction errors directly into the encrypted domain.
Achieved higher data embedding capacity than existing state-of-the-art reversible data hiding methods across both proposed approaches.
Improved reconstructed image quality upon secret data extraction and complete original image recovery.

Cite This Study

Puteaux et al. (2018) studied this question.

synapsesocial.com/papers/69d8bb48d2f7327e70ae4141 https://doi.org/10.1109/tifs.2018.2799381

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January 29, 2018IEEE Transactions on Information Forensics and SecurityOpen Access

An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images

View Full Paper

Ask AI

Bookmark

Authors

PPPauline PuteauxCentre National de la Recherche Scientifique WPWilliam PuechLaboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier

Discussion

Member takes

Overview

Algorithm evaluation demonstrates superior embedding capacity and image reconstruction quality in encrypted images, suggesting enhanced privacy protection for cloud storage.

Key Points

To develop a high-capacity reversible data hiding method for encrypted images using most significant bit prediction to enhance data privacy in cloud environments.
Designed an MSB prediction framework to embed auxiliary data into encrypted images without accessing the original image content or encryption key.
Formulated two implementation approaches: one using prediction error correction and another embedding prediction errors directly into the encrypted domain.
Achieved higher data embedding capacity than existing state-of-the-art reversible data hiding methods across both proposed approaches.
Improved reconstructed image quality upon secret data extraction and complete original image recovery.

Cite This Study

Puteaux et al. (2018) studied this question.

synapsesocial.com/papers/69d8bb48d2f7327e70ae4141 https://doi.org/10.1109/tifs.2018.2799381

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