@article{2584,
  author = {Gangyi Hu, Sumeth Yuenyong, Jian Qu, Jian Rong, Weili Kou},
  title = {A Noise-Robust Image Encryption Algorithm Based on Hyper Chaotic Cellular Neural Network},
  journal = {Journal of Digital Information Management},
  year = {2018},
  volume = {16},
  number = {5},
  doi = {https://doi.org/10.6025/jdim/2018/16/5/246-257},
  url = {http://dline.info/fpaper/jdim/v16i5/jdimv16i5_4.pdf},
  abstract = {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.},
}