针对当前置乱-扩散图像加密算法在像素位置置乱过程中存在容易遭受选择明(密)文攻击问题, 尝试利用混沌理论产生随机序列, 再进行加密, 加密过程中涉及的参数通过遗传寻优得到。此算法引入明文反馈机制到图像置乱过程中, 使得置乱效果不仅与混沌初始序列有关, 而且与明文本身也密切相关, 实现了图像特性与加密算法的有机融合。而通过在扩散加密过程中引入了明文反馈机制, 来提高算法对明文的敏感性和算法的抗选择明文及密文攻击性能, 有效融合了图像的特征信息进行加密算法设计, 使得加密算法某种程度上具有数据驱动特性。最后, 通过实验和相关分析表明, 该算法不仅可以有效抵御选择明文攻击、抵抗统计攻击及信息熵攻击, 而且还有效提高了图像加密效率, 实现图像安全传输。

In view of the present chaotic image encryption algorithm based on scrambling-diffusion, it exists in the process of pixel position scrambling vulnerable to choose plaintext (ciphertext) attack, we put forward a image encryption algorithm based on genetic-super chaotic. This algorithm introduces the explicit feedback mechanism to the image scrambling process. Its scrambling effect is not only related to the initial sequence of chaos, but also closely related to the plaintext itself. Therefore, it implements the organic integration of image characteristics and encryption algorithms. In this paper, we add the explicit feedback mechanism in the process of diffusion encryption, which improves the sensitivity of the algorithm to plaintext, and it improves the anti-selection plaintext and ciphertext attack performance. So, it uses the feature information of the image to encrypt, it also has data-driven features. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist choose plaintext (ciphertext) attack and statistical attack resistance and information entropy attack, but also effectively improve the efficiency of image encryption. It is a relatively secure and effective way of image communication.