Selective 3D Crypto-compression Method Based on Draco after Quantization
Year: 2026
Type: article
Abstract: The growing use of 3D objects in applications such as augmented and virtual reality and computer-aided design poses serious challenges in terms of compression and security, particularly during transmission, storage in the cloud, and deployment in virtual environments such as the Metaverse. 3D crypto-compression, which integrates encryption and compression, provides an efficient solution, particularly joint compression and encryption methods, which ensure data confidentiality and storage efficiency while maintaining format compliance. In this article, we present a new and efficient method of selective crypto-compression using the Draco 3D compression format. Our approach applies selective encryption just after vertex quantization, using Advanced Encryption Standard in Cipher FeedBack mode to preserve random access, and decorrelate vertex positions. We further propose an adaptive selective encryption strategy that dynamically adjusts selective encryption parameters according to the desired visual security level. In addition, we introduce an edge length distribution analysis to evaluate the statistical security of the 3D object crypto-compression method we propose. Experimental results presented on a large database demonstrate that our method achieves an optimal tradeoff between compression efficiency and security, ensuring format compliance.
DOI: 10.1145/3811915
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7161409161