With the rapid development of the metaverse, massive amounts of 3D data are created and outsourced in the cloud, and ciphertext policy attribute-based encryption (CP-ABE) is widely used in fine-grained access control to achieve secure outsourced data sharing. However, the prominent security risk is due to the fact that authorized data users may later become traitors and illegally redistribute the 3D models to the public. To protect the rights of the creator, a traitor tracing and access control method for encrypted 3D models is proposed using CP-ABE and fair watermark to meet the security needs in the metaverse. First, a commutative watermark/encryption method based on the orthogonal operation domain is designed, and the 3D model is encrypted by CP-ABE. Then, a fair watermark protocol protects the rights of the parties. Finally, the blockchain acts as a trusted third party and records the authentication information for traitor tracing. The experimental results demonstrate the feasibility and safety of the proposed method.

Reversible data hiding in encrypted domain (RDH-ED) can perform data encryption to fulfill the privacy protection of original media and embed additional data for covert communication or access control. However, current researches are focusing on the encrypted images, and little attention is paid to encrypted three-dimensional (3D) models. In this article, a high capacity separable RDH-ED method for encrypted 3D models is proposed based on octree spatial subdivision and multiple most significant bit (multi-MSB) prediction. Firstly, a 3D model is adaptively subdivided into non-overlapping subblocks by octree spatial subdivision, and the vertices in a subblock are classified into embedding set and reference set. To better utilize the spatial correlation of the two sets, the multi-MSB prediction error of the embedding set is used to embed the additional data, and the reference set is used to losslessly recover the embedded set. Then, the model is encrypted by a specified encrypted algorithm. At last, additional data is embedded into the reserved embedding room by multi-MSB substitution. Experimental results show that the proposed method can achieve a higher embedding capacity compared with the state-of-the-art methods, and guarantee the lossless recovery of the 3D model.