Journal of Engineering, Project, and Production Management, 2026, 16(6), 2025-249
Secure Documentary Lighting Synthesis and Access Control
Instructor, School of Digital Economy, Sichuan Vocational College of Chemical Technology, Luzhou, 646300, Sichuan, China, E-mail: hongyanrhy@163.com
Production Management
Received November 3, 2025; revised December 12, 2025; accepted December 14, 2025
Available online September 10, 2026
Abstract: Documentary filmmaking faces significant challenges in achieving realistic lighting conditions due to geographical constraints, equipment limitations, and environmental factors. Meanwhile, the increasing value of digital media assets necessitates robust protection mechanisms against unauthorized access and data breaches. This paper addresses the research gap at the intersection of automated scene generation and data security by proposing an integrated framework that combines Artificial Intelligence (AI)-driven lighting synthesis with comprehensive access control mechanisms. The proposed system employs a dual-network architecture comprising Generative Adversarial Networks (GANs) and Physics-Informed Neural Networks (PINNs) to generate physically accurate light-field representations, while Deep Reinforcement Learning (DRL) optimizes scene parameters using a Soft Actor-Critic algorithm. For security, the framework implements multi-layered protection, including Attribute-Based Encryption (ABE) for fine-grained access control, blockchain-based permission management using Hyperledger Fabric, and hierarchical key management with threshold cryptography. Experimental evaluation demonstrates that the system achieves high-fidelity scene generation while maintaining security resilience against multiple threat vectors, with computational overhead remaining within acceptable bounds for production workflows. The modular architecture enables independent optimization of creative and security components, providing documentary production teams with flexible tools for AI-assisted scene creation while ensuring comprehensive protection of proprietary digital assets throughout the production lifecycle.
Keywords: Light field generation; deep reinforcement learning; blockchain-based access control; attribute-based encryption; documentary production; privacy protection.
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Citation: Ran, H. (2026). Secure Documentary Lighting Synthesis and Access Control. Journal of Engineering, Project, and Production Management, 16(6), 2025-249.
