A color image encryption scheme utilizing a logistic-sine chaotic map and cellular automata.

The rapid advancement of 5G technology has led to a significant increase in the generation and transmission of visual image data, underscoring the growing need for robust privacy protection. However, existing chaotic encryption methods often suffer from simplicity and limited security because they rely on single-layer encryption approaches. To address these challenges, this paper introduces a multi-layer image encryption algorithm that leverages the Logistic-Sine chaotic Map (LSCM) and cellular automata for enhanced security. Initially, the R, G, and B channels of an image are extracted and subjected to independent row and column transformations, creating a new, scrambled matrix. Subsequently, the proposed LSCM, which integrates logistic and sine maps to overcome periodic vulnerabilities, generates a rich chaotic sequence for XOR-based encryption. Finally, cellular automata further enhance the obfuscation, increasing the algorithm's complexity and attack resistance. Experimental results demonstrate that the image encryption algorithm achieves high security, strong robustness against noise and data loss, and superior performance in statistical and correlation analyses. These findings suggest that the algorithm is well-suited for protecting visual data in networked environments, offering significant application value in image privacy and security.