A Steganographic Message Transmission Method Based on Style Transfer and Denoising Diffusion Probabilistic Model
Yen-Hui Lin, Chin-Pan Huang, Ping-Sheng Huang · Electronics · 2025
This study presents a new steganography method for message transmission based on style transfer and denoising diffusion probabilistic model (DDPM) techniques. Different types of object images are used to represent the messages and are arranged in order from left to right and top to bottom to generate a secret image. Then, the style transfer technique is employed to embed the secret image (content image) into the cover image (style image) to create a stego image. To reveal the messages, the DDPM technique is first used to inpaint the secret image from the stego image. Then, the YOLO (You Only Look Once) technique is utilized to detect objects in the secret image for the message decoding. Two security mechanisms are included: one uses object images for the message encoding, and the other hides them in a customizable public image. To obtain the messages, both mechanisms need to be cracked at the same time. Therefore, this method provides highly secure information protection. Experimental results show that our method has good confidential information transmission performance.