A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices

With the evolution of technologies, the size of an image data has been significantly increased. However, traditional image encryption schemes cannot handle the emerging problems in big data such as noise toleration and compression. In order to meet today's challenges, we propose a new image encryption scheme based on chaotic maps and orthogonal matrices. The main core of the proposed scheme is based on the interesting properties of an orthogonal matrix. To obtain a random orthogonal matrix via the Gram Schmidt algorithm, a well-known nonlinear chaotic map is used in the proposed scheme to diffuse pixels values of a plaintext image. In the process of block-wise random permutation, the logistic map is employed followed by the diffusion process. The experimental results and security analyses such as key space, differential and statistical attacks show that the proposed scheme is secure enough and robust against channel noise and JPEG compression. In addition to complete encryption for higher security, it also supports partial encryption for faster processing as well.