  As a new generation of digital media for covert transmission, three-dimension
(3D) mesh models are frequently used and distributed on the network. Facing the
huge massive of network data, it is urgent to study a method to protect and
store this large amounts of data. In this paper, we proposed a high capacity
reversible data hiding in encrypted 3D mesh models. This method divides the
vertices of all 3D mesh into "embedded sets" and "prediction sets" based on the
parity of the index. In addition, the multiple most significant bit (Multi-MSB)
prediction reserved space is used to adaptively embed secret message, and the
auxiliary information is compressed by arithmetic coding to further free up
redundant space of the 3D mesh models. We use the majority voting system(MSV)
principle to restore the original mesh model with high quality. The
experimental results show that our method achieves a higher embedding capacity
compared with state-of-the-art RDH-ED methods on 3D mesh models and can restore
the original 3D mesh models with high quality.
