Deep network-guided key map generation for lossless image encryption

In this article, a novel 4D Non-monotonic Sinusoidal Chaotic Map (NSCM) for confusion and a deep network-guided key map generation for diffusion are introduced to improve information security against various attacks. This article utilizes the advantages of the sinusoidal function to modify the monotonic function for generating random sequences to obtain a chaotic map for permutation. The limitations of substitution, such as chosen/known plaintext attacks, are suppressed using deep network-based key map generation. A key map equal in size to the size of the plaintext image is obtained as a generative output from a deep network using a smaller map and normalized to the intensity range of the plaintext image. The plaintext image is scrambled block-wise, followed by pixel-wise confusion using the chaotic map. Then the scrambled image is diffused with the key map using a bit-level XOR operation to obtain the encrypted image. The proposed method can be reversed for retrieving the plaintext image, that is, diffusion followed by confusion. The experimental results show that the proposed method performs better qualitatively in terms of visual perception as well as quantitatively in terms of entropy and Peak Signal-to-Noise Ratio (PSNR). Also, the proposed method strongly restricts various attacks such as chosen-plaintext attacks and differential attacks.