A Chaotic Scrambling and Diffusion-Based Encryption Framework for Real-Time News Video Transmission - Liu, Na (Informatica, 2025)
In the information age, news videos face growing security risks during transmission. To address this, a novel image encryption algorithm combining chaotic maps and crowd simulation is proposed. The framework integrates a dual mechanism of scrambling and diffusion to disrupt both spatial structure and pixel values. Specifically, a chaotic logistic map is employed to generate dynamic key sequences for pixel-level diffusion, while a crowd simulation algorithm produces pseudo-random sequences to control row and column scrambling. This hybrid structure enhances encryption strength and unpredictability. The experimental results show that the information entropy of the proposed model is 7.97, the pixel change rate is 99.62%, and the pixel correlation is reduced to 0.08. Decryption yields an SSIM of 0.95, while encryption and decryption take only 109 ms and 184 ms, respectively-over 50% faster than comparable models. The model exhibits high security, efficiency, and reversibility, making it well-suited for protecting sensitive news video transmissions.