Quantum Image Cryptography of Continuous Chaotic Maps by Using Pixel Shuffeling

Abstract

Images are important data carriers because, compared to text data, they are harder to transfer or store securely and include higher volumes and redundancies of digital data. Images can be shielded against a variety of risks with security, including eavesdropping and illegal copying and alteration. Because of the potential quantum risk to the existing cryptographic encryption methods and the quick advancement towards the development of quantum computers, quantum image encryption algorithms have recently drawn increasing amounts of attention. The majority of quantum image encryption techniques such as diffusion and scrambling, involve two separate rounds. In this model, the three different chaotic maps are used separately for scrambling the images to determine the performance of the quantum image cryptography with different combination of the model. At first, the hash256 algorithm is used for generating the quantum key and the forward diffusion takes place for diffusing the first pixel to final pixel of the input image information. Then, the three different chaotic maps such as pixel permutation, Chen attractor and Lorenz attractor are used for scrambling the input image. Finally, the bit-level permutation and backward diffusion process are considered for the scrambled image. For evaluating the performance of the quantum image cryptography based on the three different chaotic maps, the NPCR, UACI, Entropy, SSIM, correlation characteristics and histogram analysis are determined. The attained NPCR, UACI, Entropy and SSIM of the CASIA2 dataset for Lorenz attractor are improved than the pixel permutation and Chen attractor. Thus, from the attained values, the Quantum Image Cryptography Based on Continuous Chaotic Map such as Lorenz attractor performs better for the statistical and differential analysis than the other chaotic maps.