Chaotic color multi-image compression-encryption/ LSB data type steganography scheme for NFT transaction security - Zheyi Zhang; Yinghong Cao; Hadi Jahanshahi; Jun Mou (Journal of King Saud University: Computer and Information Sciences, 2023)
With the rapid development of blockchain technology, the security of non-fungible tokens (NFT) in the transaction process has attracted much attention. In the transaction process, the commoditized NFT images will inevitably involve display and leakage problems, which is likely to lead to economic losses drink copyright disputes between the trading parties. To protect transaction security, a chaotic color multi-image compression encryption/LSB data-type steganography scheme is proposed in the paper. A series of chaotic sequences are obtained by iterating the chaotic map, while compression sensing (CS) is introduced to compress multiple secret images and fuse the compressed secret images into one large secret image. Then this image is encrypted, and the encrypted large secret image is hidden on multiple cover images by steganography. This encryption can hide the change in the statistical properties caused by steganography. Finally, the cover image is combined with the 3D object model by using it as a texture for the 3D object model to realize the type steganography of the image data. The simulation and performance test results of the scheme illustrate that the scheme has a large enough key space and steganography capacity, as well as good resistance to differential attacks, statistical attacks, compression reconstruction quality, and robustness. This scheme can well protect the transaction security of NFT images, and at the same time open a channel connecting 2D images and 3D obj textured models, which provides a new idea for steganography.