Two neural networks which are trained on their mutual output bits are
analysed using methods of statistical physics. The exact solution of the
dynamics of the two weight vectors shows a novel phenomenon: The networks
synchronize to a state with identical time dependent weights. Extending the
models to multilayer networks with discrete weights, it is shown how
synchronization by mutual learning can be applied to secret key exchange over a
public channel.Comment: Invited talk for the meeting of the German Physical Societ