Neural cryptography: Difference between revisions

Revision as of 05:32, 23 May 2018

Revision as of 16:00, 29 May 2018

Line 3:

== Definition ==

Neural[[Artificial Networksneural network]]s are well known for their ability to selectively explore the solution space of a given problem. This feature finds a natural niche of application in the field of [[cryptanalysis]]. At the same time, Neuralneural Networksnetworks offer a new approach to attack ciphering algorithms based on the principle that any function could be reproduced by a neural network, which is a powerful proven computational tool that can be used to find the inverse-function of any cryptographic algorithm.

The ideas of mutual learning, self learning, and stochastic behavior of neural networks and similar algorithms can be used for different aspects of cryptography, like [[public-key cryptography]], solving the [[Key (cryptography)|key]] distribution problem using neural network mutual synchronization, [[Cryptographic hash function|hashing]] or generation of [[Cryptographically secure pseudo-random number generator|pseudo-random numbers]].