Robust Reversible Watermarking in Encrypted Images Based on Dual-MSBs Spiral Embedding

2026-01-20

AI Summary

This work proposes a novel framework for reversible data hiding in encrypted images that addresses the challenges of limited embedding capacity and the trade-off between robustness and reversibility. By integrating predictive error compression, dual most significant bit (dual-MSB) spiral embedding, spatial redundancy, and error-correcting codes, the method reserves embedding space through compressed prediction error bitplanes and distributes redundant watermark copies spirally within the encrypted domain. This approach ensures perfect reversibility while significantly enhancing robustness against common attacks such as Gaussian noise, JPEG compression, and cropping. Experimental results on standard test images demonstrate that the proposed scheme achieves lower bit error rates, high embedding capacity, and stable performance under various distortion conditions.

Technology Category

• Computer Vision: Adversarial Attacks & Robustness
• Machine Learning: Adversarial Learning & Robustness
• Data Mining & Knowledge Management: Data Compression

Application Category

• Security and Privacy: Applications of cryptography
• Responsible Web: Measurement, analysis, and circumvention of Web censorship
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs

Abstract

Robust reversible watermarking in encrypted images (RRWEI) faces an inherent challenge in simultaneously achieving robustness, reversibility, and content privacy under severely constrained embedding capacity. Existing RRWEI schemes often exhibit limited robustness against noise, lossy compression, and cropping attacks due to insufficient redundancy in the encrypted domain. To address this challenge, this paper proposes a novel RRWEI framework that couples dual most significant bit-plane (dual-MSBs) embedding with spatial redundancy and error-correcting coding. By compressing prediction-error bit-planes, sufficient embedding space and auxiliary information for lossless reconstruction are reserved. The dual-MSBs are further reorganized using a spiral embedding strategy to distribute multiple redundant watermark copies across spatially dispersed regions, enhancing robustness against both noise and spatial loss.Experimental results on standard test images demonstrate that the proposed method consistently outperforms under evaluated settings robustness against Gaussian noise, JPEG compression, and diverse cropping attacks, while maintaining perfect reversibility and high embedding capacity. Compared with state-of-the-art RRWEI schemes, the proposed framework achieves substantially lower bit-error rates and more stable performance under a wide range of attack scenarios.

Problem

• Robust reversible watermarking
• Encrypted images
• Embedding capacity
• Content privacy
• Robustness

Innovation

• Reversible Watermarking
• Encrypted Images
• Dual-MSBs Embedding
• Spiral Embedding
• Error-Correcting Coding