Design and Implementation of Stream Cipher Using Neural Network - Siddeq Ameen; Mazin Othman; Safwan Hasoon; Moyed Al-Razaq (Al-Rafidain Journal of Computer Sciences and Mathematics)
The centaral problem in stream cipher cryptograph is the  the difficulty to generate a long unpredicatable sequence of binary signals from short and random key. Unpredicatable sequence are desirable in cryptography because it is impossible, given a reasonable segment of its signals and computer resources, to find out more about them. Pseudorandom bit generators have been widely used to construct these sequences. The paper presents a PN sequence generator that uses neural network. Computer simulation tests have been carried out to check  the  randomness  of the generated  through statistical tests. There tests have shown the successful PN sequence generator passes all the recommended tests. The paper also proposes and validates the data encryption and decryption process using neural network instead of using traditional methods (Exclusive or). This task increases the difficulty in the breaking the cipher.