REVERSIBLE WATERMARKING ALGORITHM WITH CHAOS AND ZUC ENCRYPTION BASED ON DEEP LEARNING IN HEALTHCARE

Abstract

In view of the shortcomings of the existing reversible watermarking algorithms for encrypted images, such as low embedding rate and incomplete separation, and at the same time ensuring the embedding rate and the quality of the watermarked image, this paper proposes a reversible watermarking algorithm for encrypted images with high embedding rate and separable effect. This paper proposes a reversible watermarking algorithm for encrypted images with high embedding rate and separable effect. First, the plaintext image is encrypted by using the encryption series generated by chaotic system and Zu Chongzhi’s encryption algorithm; Second, analyze the PSNR value of the image under different interpolation conditions, generate the corresponding expected interpolation, and embed the watermark information into the image based on the expected interpolation; Finally, the original image can be recovered by using the encryption key, and the watermark information can be obtained by using the embedded key. The security and embedding ability of the algorithm are analyzed through simulation experiments. The results show that the introduction of ZUC stream cipher can expand the key space of the algorithm, have high security and achieve the separable effect. The embedding of watermark information has little impact on the ciphertext image, and the embedding rate is also higher than the contrast algorithm under the condition of ensuring the visual effect of the image.