A Visual Perception-Based Tunable Framework and Evaluation Benchmark for H.265/HEVC ROI Encryption

TL;DR

This paper introduces a visual perception-based, tunable ROI encryption framework for H.265/HEVC videos, along with a standardized evaluation benchmark to improve flexibility, security, and performance measurement.

Contribution

It presents a novel visual perception network for ROI recognition, a three-level tunable encryption strategy, and a unified benchmark for evaluating ROI encryption methods.

Findings

The benchmark effectively measures ROI encryption performance.

Enhanced encryption levels outperform existing algorithms.

The framework balances security and real-time performance.

Abstract

ROI selective encryption, as an efficient privacy protection technique, encrypts only the key regions in the video, thereby ensuring security while minimizing the impact on coding efficiency. However, existing ROI-based video encryption methods suffer from insufficient flexibility and lack of a unified evaluation system. To address these issues, we propose a visual perception-based tunable framework and evaluation benchmark for H.265/HEVC ROI encryption. Our scheme introduces three key contributions: 1) A ROI region recognition module based on visual perception network is proposed to accurately identify the ROI region in videos. 2) A three-level tunable encryption strategy is implemented while balancing security and real-time performance. 3) A unified ROI encryption evaluation benchmark is developed to provide a standardized quantitative platform for subsequent research. This triple strategy provides new solution and significant unified performance evaluation methods for ROI selective encryption field. Experimental results indicate that the proposed benchmark can comprehensively measure the performance of the ROI selective encryption. Compared to existing ROI encryption algorithms, our proposed enhanced and advanced level encryption exhibit superior performance in multiple performance metrics. In general, the proposed framework effectively meets the privacy protection requirements in H.265/HEVC and provides a reliable solution for secure and efficient processing of sensitive video content.