Chaotic Neural Network Based Pseudo-Random Sequence Generator for Cryptographic Applications

the objective of any cryptographic system is to transmit the data among the intended clients with no spillage of data to other people who may have unauthorized access to it. A typical secret key could be made over an open channel available to any opponent. As we reviewed in this paper, a cryptographically efficient pseudorandom sequence should have the characteristics of high randomness and encryption effect. Neural systems can be utilized to create common secret key. In case of neural cryptography, both the communicating systems get an indistinguishable data vector, produce an output bit and are prepared in view of the output bit. The two systems and their weight vectors show a novel phenomenon, where the systems synchronize to a state with indistinguishable time-dependent weights. The statistical quality of pseudo-random sequences determines the strength of cryptographic system. The generation of pseudo-random sequences with high randomness and encryption effect is a key challenge. We also discuss simple examples of neural network.