EFFICIENT WATERMARK EMBEDDING IN VIDEO FILES USING KEY FRAME DETECTION AND ENCRYPTION

Digital video and information authentication and IP protection need video watermarking. Due to video watermarking systems’ efficiency and speed, real-time applications and large-scale video processing typically create significant challenges. This work improves video watermarking systems by dramatically reducing their operation time. This study focuses on improving current strategies to embed and remove watermarks faster without losing resilience or perceptual quality. The proposed technique simplifies watermarking utilizing new computational approaches and algorithmic improvements. It will be more feasible for real-time applications including secure content sharing, VOD, (Video on demand) and live streaming. Using efficient data structures, novel heuristics, and parallel processing architectures reduces computer overhead. The study also uses sophisticated signal processing and machine learning to make embedded watermarks more resistant to compression, noise addition, and geometric alterations. This ensures content authenticity in various operating settings. Experimental benchmark datasets and performance measurements including computational complexity, watermark imperceptibility, and embedding capacity will test the recommended enhancements. Results will demonstrate that better approaches reduce operation time while maintaining or improving perceptual quality and robustness. This work improves video watermarking technology by increasing its practical use in current digital media ecosystems and addressing performance restrictions. Secure multimedia information distribution and protection industries think the recommended ways will be widely used since they enhance efficiency without compromising security.