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

TL;DR

This work tackles robust reversible watermarking in encrypted images (RRWEI) under severely limited embedding capacity. It introduces a framework that integrates prediction-error bit-plane compression, dual-MSBs embedding, spiral bitstream rearrangement, spread-spectrum watermarking, and Reed-Solomon-based error-correcting coding to achieve high robustness while ensuring perfect reversibility in the ciphertext domain. Experiments on BOSSbase demonstrate substantial improvements over existing RRWEI methods and plaintext-domain schemes migrated to ciphertext, including near-zero bit-error rates under moderate noise and strong resilience to cropping and JPEG compression. The approach maintains strong content confidentiality and offers practical robustness-security trade-offs for secure watermarking of encrypted multimedia.

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.

Figures (12)

• Figure 1: The overall diagram of the proposed method
• Figure 2: Diagram of Watermark Spread Spectrum Embedding
• Figure 3: Average BER under Different RS Parameters and Noise Variances
• Figure 4: Bit-flip probability versus Gaussian noise standard deviation for MSB-plane and dual-MSBs embedding schemes.
• Figure 5: Robustness under Gaussian noise attacks with different component ablations ($EC=128$ bits).