An Algorithm Based on Hodgkin-Huxley Model and Latin Square for Image Encryption

Image transmission is happening more frequently in this era of technologically sophisticated digital information. Additionally, more individuals are becoming aware of its importance. In order to secure images, many academics are participating in research, which is advantageous for guaranteeing data security. In order to strengthen the security of images during transmission, we have investigated new encryption algorithms to guarantee this. First, a current representing the Lorenz chaotic system is introduced into the neuron model. The neuron model generates sequences after receiving the current signal. The next move is made as the current shifts depending on whether the resulting sequences are chaotic or not. If so, the subsequent operation is carried out; otherwise, the current is altered until chaotic sequences are produced. Second, a global scrambling with de-duplication technique is used to scramble the image using the resulting chaotic sequences. To complete the dislocation effect, the Latin square is used to dislocate the image after the initial dislocation. Fourth, the image that has been scrambled is subjected to two rounds of additive mode diffusion. They are diffusion in the forward additive mode and diffusion in the inverse additive mode. Lastly, to improve the diffusion effect, the image is diffused in the finite domain. Eventually, the encrypted image is obtained. After evaluation tests and comparison with related literature, it can be found that the algorithm of this study has certain advantages. Also, the resistance to attack is good. It can protect the security of the image.