Exploring Device-Oriented Video Encryption for Hierarchical Privacy Protection in AR Content Sharing
🤖 AI Summary
To address multi-level privacy risks arising from physical context leakage (e.g., faces) during cross-device AR content sharing, this paper proposes a security-rating-driven hierarchical ROI video encryption framework tailored for three display modalities: projectors, smartphones, and AR glasses. It introduces ROI encryption to the AR domain for the first time and implements it as a lightweight, bitstream-level embedding within H.264/H.265 encoders. The framework features a device-adaptive dynamic encryption strength control mechanism, enabling bitstream-level ROI extraction, device-aware scheduling, and security-tiered protection. Compared to pixel-level encryption, our approach achieves a 3.2× speedup in encryption throughput and reduces storage overhead by 68%, while preserving AR real-time performance. It thus delivers fine-grained, low-overhead privacy protection for environmental background content.
Application Category
📝 Abstract
Content sharing across multiple Augmented Reality (AR) displays is becoming commonplace, enhancing team communication and collaboration through devices like smartphones and AR glasses. However, this practice raises significant privacy concerns, especially concerning the physical environment visible in AR, which may include sensitive personal details like facial features and identifiable information. Our research focuses on protecting privacy within AR environments, particularly the physical backgrounds visible during content sharing across three common AR display methods: projection, smartphone, and AR glasses. We analyze the potential privacy risks associated with each method and employ a Region Of Interest (ROI) video encryption system to hierarchically encrypt the physical backdrop based on its safety rating. This study pioneers the integration of ROI video encryption at the bitstream level within AR contexts, providing a more efficient solution than traditional pixel-level encryption by enhancing encryption speed and reducing the required space. Our adaptive system dynamically adjusts the encryption intensity based on the AR display method, ensuring tailored privacy protection.
Problem
Research questions and friction points this paper is trying to address.
Augmented Reality
Privacy Protection
Sensitive Information Leakage
Innovation
Methods, ideas, or system contributions that make the work stand out.
Video Encryption
AR Privacy Protection
Adaptive Encryption Strength
🔎 Similar Papers
No similar papers found.
