Enhancing Image Security With a Novel Chaotic System: A Focus on Multi-Face Image Encryption in Smart Applications

To ensure stringent security strategies for image information involving personal privacy during conveyance and storage, we propose an innovative multi-face privacy protection scheme based on chaos theory. Compared to single-face encryption algorithms, the proposed scheme has broader potential applications in fields such as smart cities and smart transportation. Specifically, a new spatiotemporal chaotic system named the sine-cosine coupled mapping lattice system (SCCML) is designed. It features a larger parameter domain, complexity, and profound unpredictability, yet maintains a simpler construction aimed at providing potential benefits and implementations in the field of information security. In the proposed multi-face privacy protection scheme, multiple faces within an image are rapidly and accurately identified and then encrypted using the proposed SCCML-based digital separation loop encryption algorithm. The encryption algorithm exhibits a synchronous scrambling diffusion mechanism. Additionally, the introduction of mixed multi-base cascade diffusion offers multiple layers of security for facial data, prevents diffusion singularity, and enhances diversity, making it significantly more challenging to crack. Experimental verification on a real multi-face image dataset shows that the algorithm is superior, practical, safe, and efficient.