Hybridization of Genetic Algorithm with Neural Networks to Cipher English Texts

This research aims in the first stage to built a cipher system using hybrid Genetic Algorithm with single layer Neural network to prevent any data attack during the transition process , where the ASCII of the letters are used as inputs to the network and the random numbers are used as outputs to the network , then the weights will be constructed after the network training .
In the second stage a decipher process is used to restore the ciphered data by using the inverse of the genetic neural network , where the inverse of weights is used as a key for the decryption process .
Stream cipher method is used to input the data in the network during the ciphering stage. This suggested technique attained 100% success.
All the ciphering and deciphering processes are built under MATLAB ver.(7) .