ABE-VVS: Attribute-Based Encrypted Volumetric Video Streaming

2026-01-13

AI Summary

This work addresses the high computational overhead and latency inherent in traditional point cloud video stream encryption, which struggles to balance security and efficiency. The authors propose an attribute-based selective coordinate encryption framework—ABE-X/XY/XYZ—that enables, for the first time, an end-to-end DRM-enabled point cloud streaming system. By leveraging attribute-based encryption (ABE) to selectively encrypt point cloud coordinates at a fine granularity, the approach significantly reduces computational costs while preserving content security. Compared to full-frame encryption, the ABE-X variant reduces encryption and decryption times by 50% and 80%, respectively, and lowers server and cache CPU loads by up to 80% and 63%. Moreover, the client achieves zero playback stuttering, with cache hit rates comparable to standard HTTP.

Technology Category

• Computer Vision: 3D Computer Vision
• Machine Learning: Hardware-aware ML
• Data Mining & Knowledge Management: Data Stream Mining

Application Category

• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

This work introduces ABE-VVS, a framework that performs attribute based selective coordinate encryption for point cloud based volumetric video streaming, enabling lightweight yet effective digital rights management (DRM). Rather than encrypting entire point cloud frames, our approach encrypts only selected subsets of coordinates ($X, Y, Z$, or combinations), lowering computational overhead and latency while still producing strong visual distortion that prevents meaningful unauthorized viewing. Our experiments show that encrypting only the $X$ coordinates achieves effective obfuscation while reducing encryption and decryption times by up to 50% and 80%, respectively, compared to full-frame encryption. To our knowledge, this is the first work to provide a novel end-to-end evaluation of a DRM-enabled secure point cloud streaming system. We deployed a point cloud video streaming setup on the CloudLab testbed and evaluated three HTTP-based Attribute-Based Encryption (ABE) granularities - ABE-XYZ (encrypting all $X,Y,Z$ coordinates), ABE-XY, and ABE-X against conventional HTTPS/TLS secure streaming as well as an HTTP-only baseline without any security. Our streaming evaluation demonstrates that ABE-based schemes reduce server-side CPU load by up to 80% and cache CPU load by up to 63%, comparable to HTTP-only, while maintaining similar cache hit rates. Moreover, ABE-XYZ and ABE-XY exhibit lower client-side rebuffering than HTTPS, and ABE-X achieves zero rebuffering comparable to HTTP-only. Although ABE-VVS increases client-side CPU usage, the overhead is not large enough to affect streaming quality and is offset by its broader benefits, including simplified key revocation, elimination of per-client encryption, and reduced server and cache load.

Problem

• Digital Rights Management
• Volumetric Video Streaming
• Point Cloud
• Attribute-Based Encryption
• Secure Streaming

Innovation

• Attribute-Based Encryption
• Point Cloud Streaming
• Selective Coordinate Encryption
• Digital Rights Management
• Volumetric Video