Preliminary study of applied binary neural networks for neural cryptography
Raul Valencia Tenorio, Chiu‐Wing Sham, Danilo Vargas · 2020
Adversarial neural cryptography is deemed as an encouraging area of research that could provide different perspective in the post-quantum cryptography age, specially for secure transmission of information. Nevertheless, it is still under explored with a handful of publications on the subject. This study proposes the theoretical implementation of a neuroevolved binary neural network based on boolean logic functions only (BiSUNA), with the purpose of encrypting/decrypting a payload between two agents, hiding information from a competitor.