Secure exchange of information by synchronization of neural networks

Details Secure exchange of information by synchronization of neural networks Secure exchange of information by synchronization of neural networks

2002-02-07

arxiv.org/abs/cond-mat/0202112v1

Europhys. Lett. 57, pp. 141-147 (2002

Physics

Condensed Matter

Statistical Mechanics

11 pages, 5 figures

Scientific paper

10.1209/epl/i2002-00552-9

A connection between the theory of neural networks and cryptography is presented. A new phenomenon, namely synchronization of neural networks is leading to a new method of exchange of secret messages. Numerical simulations show that two artificial networks being trained by Hebbian learning rule on their mutual outputs develop an antiparallel state of their synaptic weights. The synchronized weights are used to construct an ephemeral key exchange protocol for a secure transmission of secret data. It is shown that an opponent who knows the protocol and all details of any transmission of the data has no chance to decrypt the secret message, since tracking the weights is a hard problem compared to synchronization. The complexity of the generation of the secure channel is linear with the size of the network.

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