Neural cryptography with feedback
Disordered Systems and Neural Networks
2007-05-23 v2
Abstract
Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.
Cite
@article{arxiv.cond-mat/0311607,
title = {Neural cryptography with feedback},
author = {Andreas Ruttor and Wolfgang Kinzel and Lanir Shacham and Ido Kanter},
journal= {arXiv preprint arXiv:cond-mat/0311607},
year = {2007}
}
Comments
8 pages, 10 figures; abstract changed, references updated