What question did this study set out to answer?

To develop a high-capacity reversible data hiding algorithm for encrypted images that guarantees error-free data extraction and lossless image recovery.

August 22, 2019IEEE Transactions on MultimediaOpen Access

Reversible Data Hiding in Encrypted Images Based on Multi-MSB Prediction and Huffman Coding

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Authors

ZYZhaoxia Yin YXYouzhi Xiang XZXinpeng Zhang

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Overview

Algorithm evaluation demonstrates increased embedding capacity in encrypted images, indicating improved data concealment for secure cloud storage.

Key Points

To develop a high-capacity reversible data hiding algorithm for encrypted images that guarantees error-free data extraction and lossless image recovery.
Multi-MSB values of image pixels were adaptively predicted and marked using Huffman coding prior to encryption.
The pre-processed image was encrypted using a stream cipher technique to secure the visual content.
Additional data was embedded into the vacated storage space through multi-MSB substitution.
The proposed algorithm achieved a higher data embedding capacity compared to existing state-of-the-art methods.
The framework allowed complete error-free extraction of embedded secret payloads alongside lossless restoration of original images.

Cite This Study

Yin et al. (2019) studied this question.

synapsesocial.com/papers/69d8bb48d2f7327e70ae413e https://doi.org/10.1109/tmm.2019.2936314

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August 22, 2019IEEE Transactions on MultimediaOpen Access

Reversible Data Hiding in Encrypted Images Based on Multi-MSB Prediction and Huffman Coding

View Full Paper

Ask AI

Bookmark

Authors

ZYZhaoxia Yin YXYouzhi Xiang XZXinpeng Zhang

Discussion

Member takes

Overview

Algorithm evaluation demonstrates increased embedding capacity in encrypted images, indicating improved data concealment for secure cloud storage.

Key Points

To develop a high-capacity reversible data hiding algorithm for encrypted images that guarantees error-free data extraction and lossless image recovery.
Multi-MSB values of image pixels were adaptively predicted and marked using Huffman coding prior to encryption.
The pre-processed image was encrypted using a stream cipher technique to secure the visual content.
Additional data was embedded into the vacated storage space through multi-MSB substitution.
The proposed algorithm achieved a higher data embedding capacity compared to existing state-of-the-art methods.
The framework allowed complete error-free extraction of embedded secret payloads alongside lossless restoration of original images.

Cite This Study

Yin et al. (2019) studied this question.

synapsesocial.com/papers/69d8bb48d2f7327e70ae413e https://doi.org/10.1109/tmm.2019.2936314

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