A high-capacity adaptive steganographic encryption algorithm for NFT images based on HPM hyperchaotic map-driven bidirectional spiral scrambling and dynamic Morse code diffusion

Non-fungible token (NFT) images, with their uniqueness enabled by blockchain, are transforming from technological experiments into core assets that drive digital art and the metaverse economy. However, an important pain point of NFT images is the risk of leakage during transmission. This paper introduces an adaptive capacity low-bit steganography method for NFT image encryption based on bidirectional spiral scrambling and dynamic Morse code diffusion driven by hyperbolic phase-modulated chaotic map (HPM) hyperchaotic system. The HPM hyperchaotic system with double positive Lyapunov exponents has stronger cryptographic resistance and dynamic unpredictability than the traditional two-dimensional systems with only a single positive Lyapunov exponents. The bidirectional spiral scrambling method only takes O(N) time complexity to achieve complete visual scrambling of the secret image, where N is the total number of pixels to be permuted. The chaotic sequence, processed by a multi-level dynamic encoding module and linear confusion, is subsequently XORed with the permuted NFT image to achieve pixel value diffusion. This step completely dissolves the connection between pixels and completes the encryption of the NFT image. The chaotic sequence is used as an index to embed the adaptive capacity of the encrypted image into the low bits of the pixel value of the cover image. Chaotic encrypted of NFT images and embedded them into cover images using low-bit steganography technology can achieve covert transmission, evade network sniffing, and reduce the risk of leakage. Relevant experimental results show that at a high embedding capacity of 6.0 bpp, the Peak Signal-to-Noise Ratio (PSNR) is greater than 44.0 and the Structural Similarity Index (SSIM) is greater than 0.97, which meets the security requirements of financial data encryption. It not only ensures the quality of the stego image, but also enhances the robustness of the embedded information. At the same time, the encrypted steganography algorithm has significant resistance to common attacks such as cropping and salt and pepper noise, ensuring that the embedded information can still be effectively extracted in an interference environment.