Secure and Reversible Thumbnail-Preserving Encryption for Point Clouds via Spatial Subdivision and Chaotic Perturbation
Tz-Yi You, Yu-Ting Huang, Ting-Yu Hsiao, Yung-Wen Cheng, Yuan‐Yu Tsai, Ching‐Ta Lu · Mathematics · 2025
Thumbnail-preserving encryption (TPE) aims to balance data security and usability by allowing encrypted content to retain a coarse visual preview while protecting sensitive details. While existing TPE techniques primarily target 2D images, effective and reversible TPE for 3D point clouds remains underexplored. This paper proposes a thumbnail-preserving encryption framework specifically designed for point clouds, addressing the challenges arising from irregular spatial structure and viewpoint-dependent visualization. The proposed method integrates perception-guided spatial subdivision with key-dependent chaotic perturbation to obfuscate fine-grained geometric details while intentionally preserving coarse structural information under the TPE threat model. A reversible integer-domain design is further incorporated to enable exact recovery of the original point cloud and support reversible data hiding by exploiting coordinate-level redundancy. Extensive experiments conducted on diverse point clouds demonstrate that the proposed framework maintains stable thumbnail fidelity across different viewing conditions, achieving high structural similarity, while guaranteeing perfect reversibility with zero reconstruction error. In contrast to existing image-based TPE frameworks, the proposed method extends the TPE paradigm to 3D point clouds by providing full reversibility, auxiliary message embedding support, and stable thumbnail fidelity under varying viewing conditions. Quantitative results demonstrate that thumbnail-level structural similarity is well preserved, while the original point clouds are exactly recovered after decryption.