A novel spectrogram visual security encryption algorithm based on block compressed sensing and five-dimensional chaotic system

Based on block compressed sensing theory, combined with a five-dimensional chaotic system, we propose and analyze a novel spectrogram visual security encryption algorithm. This research is devoted to solving the compression, encryption and steganography problems of spectrograms involving large data volumes and high complexity. First, the discrete wavelet transform is applied to the spectrogram to generate the coefficient matrix. Then, block compressed sensing is applied to compress and preencrypt the spectrogram. Second, we design a new five-dimensional chaotic system. Then, several typical evaluation methods, such as the phase diagram, Lyapunov exponent, bifurcation diagram and sample entropy, are applied to deeply analyze the chaotic behavior and dynamic performance of the system. Moreover, the corresponding Simulink model has been built, which proves the realizability of the chaotic system. Importantly, the measurement matrix required for compressed sensing is constructed by the chaotic sequence. Third, dynamic Josephus scrambling and annular diffusion are performed on the secret image to obtain the cipher image. Finally, an improved least significant bit embedding method and alpha channel synchronous embedding are designed to obtain a steganographic image with visual security properties. To make the initial keys of each image completely different from other images, the required keys are produced using the SHA-256 algorithm. The experimental results confirm that the visual security cryptosystem designed in this study has better compression performance, visual security and reconstruction quality. Furthermore, it is able to effectively defend against a variety of conventional attack methods, such as statistical attacks and entropy attacks.