Duple Color Image Encryption System Based on 3-D Nonequilateral Arnold Transform for IIoT - Huang, Huiqing; Cai, Zhanchuan (IEEE transactions on industrial informatics, 2023)
In the era of Industrial Internet of Things (IIoT), huge amounts of data are generated, which contains sensitive information. Therefore, how to protect data security is an important challenge in the development of IIoT. To this end, we propose a duple color image encryption method for IIoT. Different from the traditional algorithm that encrypts one plain image into one ciphertext image, our algorithm encrypts two color images into one color ciphertext image which can cause great confusion to the attacker who illegally breaks the ciphertext image. First, the proposed algorithm converts two color images with [Formula Omitted] into a 3-D bit-level matrix with [Formula Omitted]. Next, 3-D nonequilateral Arnold transform (3D-NEAT) is applied to permutate the positions of the elements of the resulted 3-D bit-level matrix. Then, the permutated 3-D bit-level matrix is transformed into three 2-D pixel-level images and then diffused by the random diffusion sequences that 3-D Lorenz system (3D-LS) generates. Finally, the scrambling matrices generated by 3D-LS are used to scramble three diffused 2-D pixel-level images, and the output is considered as three color components of the encrypted image. The numerical experiments and security analyses show that the proposed image encryption scheme has strong resistance to several known attacks, and yields near-zero correlation and near-eight entropy for the RGB cipher image, and its performance is better than some of the recently proposed image encryption algorithms.