Neural Cryptography

TL;DR

This paper introduces a novel neural cryptography method where two neural networks synchronize through mutual learning, enabling secure secret key exchange over a public channel, leveraging their synchronized weights.

Contribution

The paper demonstrates how neural network synchronization can be utilized for cryptographic key exchange, a novel application of mutual learning in neural networks.

Findings

Neural networks can synchronize through mutual learning.

Synchronization enables secure key exchange over public channels.

The method provides a new approach to cryptography using neural networks.

Abstract

Two neural networks which are trained on their mutual output bits show a novel phenomenon: The networks synchronize to a state with identical time dependent weights. It is shown how synchronization by mutual learning can be applied to cryptography: secret key exchange over a public channel.