A Large-Capacity Coverless Steganography Based on Two-MSB and Artificial Immune System

With the development of information hiding technology, coverless steganography, which provides non-embedding and distortion-free hiding by constructing a mapping relationship between the secret information and the cover image, has attracted more and more attention. This paper proposes a large-capacity coverless steganography based on two-MSB (MSB and second MSB) and Artificial Immune System (AIS). In order to use the two-Msbto represent feature information, the cover image is first divided into blocks and the pixel value of each block is averaged. Then, randomly scramble blocks to obtain the feature sequence. Next, according to the hidden ratio, a diffusion factor is introduced and optimized by an artificial immune algorithm to generate the optimal feature sequence. Finally, the mapping relationship between the optimal feature sequence and the secret information is established, and an error map is generated in the process. Experimental results show that the proposed method has good robustness and can resist attacks such as noise and filtering. Compared with existing coverless steganography algorithms, this method has higher hiding capacity and security.