Neural Cryptography - Applications

Applications

There currently no practical applications due to the recent development of the field, but it could be used specially where the keys are continually generated and the system (both pairs and the insecure media) is in a continuously evolving mode.
In 1995, Sebastien Dourlens applied neural networks cryptanalyze DES by allowing the networks to learn how to invert the S-tables of the DES. The bias in DES studied through Differential Cryptanalysis by Adi Shamir is highlighted. The experiment shows about 50% of the key bits can be found, allowing the complete key to be found in a short time. Hardware application with multi micro-controllers have been proposed due to the easy implementation of multilayer neural networks in hardware.
One example of public-key protocol is given by Khalil Shihab. He describes the decryption scheme and the public key creation that are based on a backpropagation neural network. The encryption scheme and the private key creation process are based on Boolean algebra. This technique has the advantage of small time and memory complexities. A disadvantage is the property of backpropagation algorithm: By huge training sets lasts the learning of neural network very long. Therefore the use of this protocol is only theoretical so far.