2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/22781Neural 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.8 pages, 10 figures; abstract changed, references updatedDisordered Systems and Neural Networkstext