A Noise-Robust Image Encryption Algorithm Based on Hyper Chaotic Cellular Neural Network-

We propose an image encryption algorithm based on a 6-dimensional chaotic cellular neural network (CNN) that is robust to noise/missing pixels in the cipher image. We performed parameter search on the templates of the CNN in order to discover the parameters that leads to 6D chaotic evolution of the state, and then used the resulting chaotic sequence as the basis of encryption. The encryption process itself consists of shuffling the positions of image pixels based on the numerical value of the chaotic sequence; the second half of the encryption process consists of changing the shuffled image pixel values by performing XOR operation between the pixel values and the numerical value of the chaotic sequence. By using simple operations like sorting and XOR in the encryption process, the algorithm is robust to noise/ missing pixels in the cipher image. We illustrate this by comparing the robustness against 3 recently proposed chaos-based image encryption algorithms. The results show that our algorithm is competitive with the state-ofthe-art in term of encryption security, and superior in term of robustness.