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Real-Time Bit-Level Encryption of Full High-Definition Video Without Diffusion

Dong Jiang, Hui-ran Luo, Zi-jian Cui, Xi-jue Zhao, Lin-sheng Huang, Liang-liang Lu

TL;DR

This work tackles the difficulty of achieving real-time, high-throughput video encryption with diffusion-based schemes by introducing a diffusion-free protocol that uses SHA-256 frame hashes to seed Lorenz hyperchaotic systems, enabling per-frame initialization of data-generation streams. Data for confusion and XOR operations is produced in parallel by CPU workers and deployed to a dedicated GPU thread per pixel-channel for pixel-wise encryption, achieving plaintext sensitivity with a single round and removing diffusion bottlenecks. Empirical results show delay-free encryption at 1080p/30FPS on a server (25.84 ms average) and robust performance on embedded hardware (≈28.76 ms), along with strong statistical properties (uniform histograms, decorrelation, high entropy) and resilience to brute-force, differential, cropping, and channel-noise attacks. The approach yields a dynamically expanding key space, excellent parallelism, and practical viability for real-time secure video monitoring across diverse computing platforms.

Abstract

Despite the widespread adoption of Shannon's confusion-diffusion architecture in image encryption, the implementation of diffusion to sequentially establish inter-pixel dependencies for attaining plaintext sensitivity constrains algorithmic parallelism, while the execution of multiple rounds of diffusion operations to meet the required sensitivity metrics incurs excessive computational overhead. Consequently, the pursuit of plaintext sensitivity through diffusion operations is the primary factor limiting the computational efficiency and throughput of video encryption algorithms, rendering them inadequate to meet the demands of real-time encryption for high-resolution video. To address the performance limitation, this paper proposes a real-time video encryption protocol based on heterogeneous parallel computing, which incorporates the SHA-256 hashes of original frames as input, employs multiple CPU threads to concurrently generate encryption-related data, and deploys numerous GPU threads to simultaneously encrypt pixels. By leveraging the extreme input sensitivity of the SHA hash, the proposed protocol achieves the required plaintext sensitivity metrics with only a single round of confusion and XOR operations, significantly reducing computational overhead. Furthermore, through eliminating the reliance on diffusion, it realizes the allocation of a dedicated GPU thread for encrypting each pixel within every channel, effectively enhancing algorithm's parallelism. The experimental results demonstrate that our approach not only exhibits superior statistical properties and robust security but also achieving delay-free bit-level encryption for 1920$\times$1080 resolution (full high definition) video at 30 FPS, with an average encryption time of 25.84 ms on a server equipped with an Intel Xeon Gold 6226R CPU and an NVIDIA GeForce RTX 3090 GPU.

Real-Time Bit-Level Encryption of Full High-Definition Video Without Diffusion

TL;DR

This work tackles the difficulty of achieving real-time, high-throughput video encryption with diffusion-based schemes by introducing a diffusion-free protocol that uses SHA-256 frame hashes to seed Lorenz hyperchaotic systems, enabling per-frame initialization of data-generation streams. Data for confusion and XOR operations is produced in parallel by CPU workers and deployed to a dedicated GPU thread per pixel-channel for pixel-wise encryption, achieving plaintext sensitivity with a single round and removing diffusion bottlenecks. Empirical results show delay-free encryption at 1080p/30FPS on a server (25.84 ms average) and robust performance on embedded hardware (≈28.76 ms), along with strong statistical properties (uniform histograms, decorrelation, high entropy) and resilience to brute-force, differential, cropping, and channel-noise attacks. The approach yields a dynamically expanding key space, excellent parallelism, and practical viability for real-time secure video monitoring across diverse computing platforms.

Abstract

Despite the widespread adoption of Shannon's confusion-diffusion architecture in image encryption, the implementation of diffusion to sequentially establish inter-pixel dependencies for attaining plaintext sensitivity constrains algorithmic parallelism, while the execution of multiple rounds of diffusion operations to meet the required sensitivity metrics incurs excessive computational overhead. Consequently, the pursuit of plaintext sensitivity through diffusion operations is the primary factor limiting the computational efficiency and throughput of video encryption algorithms, rendering them inadequate to meet the demands of real-time encryption for high-resolution video. To address the performance limitation, this paper proposes a real-time video encryption protocol based on heterogeneous parallel computing, which incorporates the SHA-256 hashes of original frames as input, employs multiple CPU threads to concurrently generate encryption-related data, and deploys numerous GPU threads to simultaneously encrypt pixels. By leveraging the extreme input sensitivity of the SHA hash, the proposed protocol achieves the required plaintext sensitivity metrics with only a single round of confusion and XOR operations, significantly reducing computational overhead. Furthermore, through eliminating the reliance on diffusion, it realizes the allocation of a dedicated GPU thread for encrypting each pixel within every channel, effectively enhancing algorithm's parallelism. The experimental results demonstrate that our approach not only exhibits superior statistical properties and robust security but also achieving delay-free bit-level encryption for 19201080 resolution (full high definition) video at 30 FPS, with an average encryption time of 25.84 ms on a server equipped with an Intel Xeon Gold 6226R CPU and an NVIDIA GeForce RTX 3090 GPU.
Paper Structure (20 sections, 16 equations, 21 figures, 9 tables)

This paper contains 20 sections, 16 equations, 21 figures, 9 tables.

Table of Contents

  1. Introduction
  2. Protocol description
  3. Initial condition reconstruction
  4. Data generation
  5. Frame encryption
  6. Algorithmic descriptions
  7. Statistical evaluation
  8. Uniformity evaluation
  9. Correlation evaluation
  10. Randomness evaluation
  11. Security analysis
  12. Resistance to brute-force attacks
  13. Resistance to differential attacks
  14. Resistance to cropping attacks and channel noise
  15. Application, encryption speed evaluation, and comparison
  16. ...and 5 more sections

Figures (21)

  • Figure 1: The workflow diagrams of initial condition reconstruction and shift distance generation.
  • Figure 2: The workflow diagram of the proposed protocol(R: red, G: green, B: blue, H: horizontal, V: vertical, $w$: width, $h$: height.)
  • Figure 3: Video encryption algorithm for the main thread $T_m$.
  • Figure 4: Data generation algorithm for worker thread $T_w^i$.
  • Figure 5: Bit extraction algorithm for GPU thread $T_g^c(i,j)$
  • ...and 16 more figures