New S-box calculation approach for Rijndael-AES based on an artificial neural network

Abstract

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.

Novel Low-Power Construction of Chaotic S-Box in Multilayer Perceptron

“…In previous studies, there is a scheme to apply S-box to multilayer perceptron. Arrañaga et al proposed a scheme that S-box can apply it to multilayer perceptron [ 17 ]. But it does not test the cryptographic characteristics of the implemented S-box, nor is it applied to the replacement of image processing.…”