3D Point Cloud Encryption through Chaotic Mapping

Xin Jin*, Zhaoxing Wu, Chenggen Song, Chunwei Zhang, Xiaodong Li*

Beijing Electronic Science and Technology Institute, 100070,Beijing, China

GOCPCCC Key Laboratory of Information Security, 100070,Beijing, China

*Corresponding Authors: {jinxin,lxd}@besti.edu.cn


    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.




                                                                                                                    Original Point Clouds   Encrypted by RV   Encrypted by RTM

The simulation results. We test our method on 3D point clouds with various contents including animal, plant, text, car etc. The left is the original point clouds. The middle is the encrypted results by the Random Vector scheme (RV) as described in Section 3.1. The Right is the encrypted results by the Random Transformation Matrix (RTM) as described in Section 3.2.  

Paper and Slides

, , , , :3D Point Cloud Encryption Through Chaotic Mapping. PCM (1) : 119-129.




  author    = {Xin Jin and
               Zhaoxing Wu and
               Chenggen Song and
               Chunwei Zhang and
               Xiaodong Li},
  title     = {3D Point Cloud Encryption Through Chaotic Mapping},
  booktitle = {Advances in Multimedia Information Processing - {PCM} 2016 - 17th
               Pacific-Rim Conference on Multimedia, Xi'an, China, September 15-16,
               2016, Proceedings, Part {I}},
  pages     = {119--129},
  year      = {2016},
  crossref  = {DBLP:conf/pcm/2016-1},
  url       = {https://doi.org/10.1007/978-3-319-48890-5_12},
  doi       = {10.1007/978-3-319-48890-5_12},
  timestamp = {Sun, 21 May 2017 00:20:54 +0200},
  biburl    = {http://dblp.uni-trier.de/rec/bib/conf/pcm/JinWSZL16},
  bibsource = {dblp computer science bibliography, http://dblp.org}


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