High-Capacity Framework for Reversible Data Hiding in Encrypted Image Using Pixel Predictions and Entropy Encoding
Yingqiang Qiu, Qichao Ying, Yuyan Yang, Huanqiang Zeng, Sheng Li, and, Zhenxing Qian

TL;DR
This paper introduces a high-capacity reversible data hiding framework for encrypted images, utilizing pixel prediction and entropy encoding to significantly improve embedding capacity and security in both VRBE and VRAE scenarios.
Contribution
It proposes a generalized high-capacity RDHEI framework with an efficient embedding room generation algorithm applicable to both VRBE and VRAE, outperforming existing methods.
Findings
Outperforms state-of-the-art RDHEI schemes in capacity and security.
Achieves error-free data extraction and image recovery with different authentication keys.
Ensures high security, making original images difficult to detect from encrypted data.
Abstract
While the existing vacating room before encryption (VRBE) based schemes can achieve decent embedding rate, the payloads of the existing vacating room after encryption (VRAE) based schemes are relatively low. To address this issue, this paper proposes a generalized framework for high-capacity RDHEI for both VRBE and VRAE cases. First, an efficient embedding room generation algorithm (ERGA) is designed to produce large embedding room by using pixel prediction and entropy encoding. Then, we propose two RDHEI schemes, one for VRBE, another for VRAE. In the VRBE scenario, the image owner generates the embedding room with ERGA and encrypts the preprocessed image by using the stream cipher with two encryption keys. Then, the data hider locates the embedding room and embeds the encrypted additional data. In the VRAE scenario, the cover image is encrypted by an improved block modulation and…
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Chaos-based Image/Signal Encryption · Digital Media Forensic Detection
