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== Applications ==
In 1995, Sebastien Dourlens applied neural networks to cryptanalyze [[Data Encryption Standard|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.{{Citation needed|date=May 2025}}
One example of a public-key protocol is given by Khalil Shihab {{Citation needed|date=May 2025}}. 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 algorithms: because of huge training sets, the learning phase of a neural network is very long. Therefore, the use of this protocol is only theoretical so far.
== Neural key exchange protocol ==
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