Neural cryptography with feedback.
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.
Ruttor
Andreas
A
Institut für Theoretische Physik, Universität Würzburg, Am Hubland, 97074 Würzburg, Germany.
Kinzel
Wolfgang
W
Shacham
Lanir
L
Kanter
Ido
I