Multifunctional Neuron-Based Secure and Efficient Encryption Scheme for Remote Sensing Imaging

With the continuous advancement of remote sensing imaging technology, the resolution of images has significantly improved, and their applications have expanded to military reconnaissance, environmental monitoring, resource surveys, and other critical domains. Traditional encryption algorithms often suffer from high computational complexity, limited real-time performance, and inadequate resistance to attacks when encrypting large-sized, highly correlated remote sensing image data. To address these challenges, this paper proposes a highly secure image encryption algorithm based on a multifunctional neuron and a dynamic S-box mechanism. First, the pixel positions of the image are scrambled using a zigzag algorithm. Subsequently, chaotic sequences generated by the multifunctional neuron are employed to diffuse the pixel values. Furthermore, a dynamic S-box constructed from these chaotic sequences is applied to enhance the diffusion effect of the image pixels. The experimental results demonstrate that the proposed encryption scheme can effectively resist exhaustive, statistical, and differential attacks. This research will provide a theoretical framework and a research methodology for the secure transmission of remote sensing images.