Efficient neural chaotic generator for image encryption

In this paper, we propose a new implementation of chaotic generator using artificial neural network. Neural network can act as an efficient source of perturbation in the chaotic generator which increases the cycleʼs length, and thus avoid the dynamical degradation due to the used finite dimensional space. On the other hand, the use of neural network enlarges the key space of the chaotic generator in an enormous way. The efficiency of the proposed neural chaotic generator is illustrated using some dynamical and NIST statistical tests. We also propose in this paper, a new image encryption method based on chaotic sequence, and the obtained results emphasize the efficiency of our technique.