This Demonstration shows how a neural-network key exchange protocol for encrypted communication works using the Hebbian learning rule. The idea is: the person A wants to communicate with the person B, but they cannot exchange a key through a secure channel, so they set two topologically identical neural networks and evaluate them with the same inputs until the weights of their respective networks match.
The "epoch" slider moves the system in time through the trained epochs while the "randomize" button creates a new configuration of the network. The system is said to be "paired" when the weights of both networks match. These networks are trained through 1000 epochs only and they may get stuck in a local minima state, so they may never come to a paired state.