Crypto-space reversible data hiding for 3D mesh models with k-Degree neighbor diffusion

Abstract

Reversible data hiding in crypto-space secures the cover media through encryption for privacy protection and provides an additional payload for embedding data management information, enabling covert communication or access control. However, the existing research reports mainly focus on the cover media of digital images, with scant attention to 3D mesh models. In this paper, we propose a separable and reversible data hiding scheme based on a novel k-degree neighbor diffusion strategy for encrypted 3D mesh models (RDHEM). By considering the model scale and the topological configuration between vertices, the proposed scheme finds an adaptive and unique solution for model vertex grouping, effectively boosting the utilization rate of model vertices for data embedding. Experimental results show that our scheme outperforms state-of-the-art schemes in both data embedding capacity and vertex utilization rate.