Securing Immersive 360 Video Streams through Attribute-Based Selective Encryption

TL;DR

This paper introduces a novel attribute-based selective encryption framework for 360-degree video streaming that enhances security and efficiency by encrypting critical viewports dynamically, outperforming traditional HTTPS methods.

Contribution

It presents a new ABE-based selective encryption approach combined with viewport-adaptive encryption for secure, scalable 360 video streaming.

Findings

Reduces computational load on caches

Improves cache hit rates

Maintains visual quality comparable to HTTPS

Abstract

Delivering high-quality, secure 360{\deg} video content introduces unique challenges, primarily due to the high bitrates and interactive demands of immersive media. Traditional HTTPS-based methods, although widely used, face limitations in computational efficiency and scalability when securing these high-resolution streams. To address these issues, this paper proposes a novel framework integrating Attribute-Based Encryption (ABE) with selective encryption techniques tailored specifically for tiled 360{\deg} video streaming. Our approach employs selective encryption of frames at varying levels to reduce computational overhead while ensuring robust protection against unauthorized access. Moreover, we explore viewport-adaptive encryption, dynamically encrypting more frames within tiles occupying larger portions of the viewer's field of view. This targeted method significantly enhances security in critical viewing areas without unnecessary overhead in peripheral regions. We deploy and evaluate our proposed approach using the CloudLab testbed, comparing its performance against traditional HTTPS streaming. Experimental results demonstrate that our ABE-based model achieves reduced computational load on intermediate caches, improves cache hit rates, and maintains comparable visual quality to HTTPS, as assessed by Video Multimethod Assessment Fusion (VMAF).