The S-box is a basic important component in symmetric key encryption, used in block ciphers to confuse or hide the relationship between the plaintext and the ciphertext. In this paper a way to develop the transformation of an input of the S-box specified in AES encryption system through an artificial neural network and the multiplicative inverse in Galois Field is presented. With this implementation more security is achieved since the values of the S-box remain hidden and the inverse table serves as a distractor since it would appear to be the complete S-box. This is implemented on MATLAB and HSPICE using a network of perceptron neurons with a hidden layer and null error.