3D Point Cloud Encryption Through Chaotic Mapping

Three dimensional (3D) contents such as 3D point clouds, 3D meshes and 3D surface models are increasingly growing and being widely spread into the industry and our daily life. However, less people consider the problem of the privacy preserving of 3D contents. As an attempt towards 3D security, in this papers, we propose methods of encrypting the 3D point clouds through chaotic mapping. 2 schemes of encryption using chaotic mapping have been proposed to encrypt 3D point clouds. (1) 3 random sequences are generated by the logistic chaotic mapping. Each random vector is sorted to randomly shuffler each coordinate of the 3D point clouds. (2) A random 3×3 invertible rotation matrix and a 3×1 translate vector are generated by the logistic mapping. Then each 3D point is projected to another random place using the above random rotation matrix and translate vector in the homogeneous coordinate. We test the above 2 encryption schemes of 3D point cloud encryption using various 3D point clouds. The 3D point clouds can be encrypted and decrypted correctly. In addition, we evaluated the encryption results by VFH (Viewpoint Feature Histogram). The experimental results show that our proposed methods can produce nearly un-recognized encrypted results of 3D point clouds.