The invention discloses an image steganography method and system for automatically learning distortion based on a GAN network structure, and the method comprises the steps: inputting an enhanced carrier image into a preset improved U-Net network, sequentially generating an initial pixel change probability graph and an initial secret-containing image, inputting the initial secret-containing image into a discrimination network, and obtaining a discrimination result, calculating the loss of the discrimination network according to the discrimination result, calculating a total loss function of the generative network according to the discrimination result and the current steganography capacity, optimizing the generative adversarial network by taking minimization of the loss function as a target, when the loss is reduced and kept stable, considering that the training is ended, extracting the generative network from the generative adversarial network after the training is ended, and inputting a to-be-transmitted original image into the generative network to obtain a pixel change probability, calculating embedded distortion corresponding to the pixel change probability, and coding the secret information and the to-be-transmitted original image by adopting a syndrome matrix coding technology according to the embedded distortion to obtain a steganographic image corresponding to the original image.