The project is aimed to implement artificial neural network method in cryptography. Cryptography is a technique to encrypt simple message into cipher text for secure transmission over any channel. The training of the network has been done using the input output set generated by the cryptosystem, which include shift and RSA ciphers. The training patterns are observed and analyzed by varying the parameters of Levenberg Marquand method and the number of neurons in the hidden layer. Using the converged network, the model is first trained, and one may obtain the desired result with required accuracy. In this respect, simulations are shown to validate the proposed model. As such, the investigation gives an idea to use the trained neural network for encryption and decryption in cryptography
