Adversarial Neuro Encoding with Binary Neural Networks

摘要

Adversarial neuro encoding could provide new insights for ciphering information with different perspectives. Nevertheless, it is still underexplored with a handful of publications on the subject. This work proposes the implementation of neuroevolved binary neural networks based on boolean logic functions only (BiSUNA) that apply payload ciphering between two agents to disperse information from an observer. The BiSUNA framework provides three distinctive attributions: it uses an adversarial neural encoding environment to improve the system data transmission; one execution yields a diversity of results given its population heuristics; lastly, it is an unconventional proposal to employ binary neural networks for the solution of symmetric ciphered problems.