Multi-level Chaotic Maps for 3D Textured Model Encryption
This work addresses the protection of 3D models for applications in Virtual Reality and Augmented Reality, presenting an incremental improvement over previous encryption methods.
The paper tackles the problem of encrypting 3D textured models by proposing a multi-level chaotic maps approach that uses different encryption methods based on the recognition contributions of vertices, polygons, and textures, resulting in similar performance to existing methods but with less time and improved resistance to attacks like statistic, brute-force, and correlation attacks.
With rapid progress of Virtual Reality and Augmented Reality technologies, 3D contents are the next widespread media in many applications. Thus, the protection of 3D models is primarily important. Encryption of 3D models is essential to maintain confidentiality. Previous work on encryption of 3D surface model often consider the point clouds, the meshes and the textures individually. In this work, a multi-level chaotic maps models for 3D textured encryption was presented by observing the different contributions for recognizing cipher 3D models between vertices (point cloud), polygons and textures. For vertices which make main contribution for recognizing, we use high level 3D Lu chaotic map to encrypt them. For polygons and textures which make relatively smaller contributions for recognizing, we use 2D Arnold's cat map and 1D Logistic map to encrypt them, respectively. The experimental results show that our method can get similar performance with the other method use the same high level chaotic map for point cloud, polygons and textures, while we use less time. Besides, our method can resist more method of attacks such as statistic attack, brute-force attack, correlation attack.