结合图像加密与深度学习的高容量图像隐写算法

High-capacity image steganography algorithm combining image encryption and deep learning

针对基于深度学习的高容量图像隐写方案存在的载体图像和含密图像的残差图像会暴露秘密图像的问题,提出了结合图像加密和深度学习的高容量图像隐写算法。该算法设计使用了一种图像特征提取方法,使得从载体图像中提取的特征与从含密图像中提取的特征是一致的。发送方在图像隐写前,从载体图像中提取特征作为密钥,用来加密秘密图像。提取方提取加密过的秘密图像后,从含密图像中提取特征作为密钥,用来解密秘密图像。实验结果表明,攻击者无法从残差图像中发现秘密图像的信息,且密钥传递的频率更低,算法安全性得到了提升。

Aiming at the problem that the residual image of cover image and carrier image in the high-capacity image steganography scheme based on deep learning will expose the secret image,a high-capacity image steganography scheme combining image encryption and deep learning was proposed.An image feature extraction method was used,so that the features extracted from the cover image were consistent with the features extracted from the carrier image.Before the image steganography,the sender extracted features from the cover image as a key to encrypt the secret image.After the extractor extracted the encrypted secret image,the features were extracted from the carrier image as a key to decrypt the secret image.The experimental results show that the attacker cannot find the information of the secret image from the residual image,and the frequency of key transmission is lower,and the security of the algorithm is improved.