Multimedia data encryption is an ever-growing and challenging domain in the emerging digital world, with image encryption at the forefront to provide privacy for the user’s data. Image encryption aims to generate a stable noisy image irrespective of the input image. The current solution to this communication challenge is to use complex mathematics with a series of algorithms known as public-key cryptography. But the increasing power of computers and the ingenuity of hackers is open up more and more cracks in this mathematical armor. An ideal solution to this problem would provide provable information security, guaranteeing the safety of our personal information. In addition to it, the system must adapt itself to day to day miracles of the real world. Neural assisted techniques are the solutions to satisfy the above-said requirements. Hence, this paper proposes Hopfield neural attractor-assisted image encryption scheme in which combined tent maps are employed for the substitution process. Nowadays, a chosen-plaintext attack is a big challenge for encryption schemes. To resist the chosen plaintext attack, this scheme proposes the higher bitplane confusion using the tent map, which replaces the conventional diffusion process. Besides, the proposed scheme offers desire metrics such as the average correlation of 0.003, entropy as 7.99, and keyspace of 10¹⁸⁴.

多媒体数据加密在新兴的数字世界中是一个不断发展且充满挑战的领域，其中图像加密处于最前沿，可为用户数据提供隐私。图像加密旨在生成稳定的噪点图像，而与输入图像无关。解决此通信难题的当前解决方案是将复杂的数学与一系列称为公钥加密的算法一起使用。但是，计算机功能的增强和黑客的聪明才智使这种数学装甲越来越多。解决此问题的理想解决方案将提供可证明的信息安全性，从而确保我们个人信息的安全。除此之外，系统还必须适应现实世界的日常奇迹。神经辅助技术是满足上述要求的解决方案。因此，本文提出了一种Hopfield神经吸引子辅助图像加密方案，该方案采用组合的帐篷图进行替换。如今，选择明文攻击已成为加密方案的一大挑战。为了抵抗选择的明文攻击，该方案使用帐篷映射图提出了更高的位平面混淆，从而取代了传统的扩散过程。此外，该方案还提供了期望度量，例如平均相关性为0.003，熵为7.99，键空间为10 取代了传统的扩散工艺。此外，该方案还提供了期望度量，例如平均相关性为0.003，熵为7.99，键空间为10 取代了传统的扩散工艺。此外，该方案还提供了期望度量，例如平均相关性为0.003，熵为7.99，键空间为10¹⁸⁴。