Systems and methods for providing enhanced multi-layered security with encryption models that improve zero-trust architectures

Abstract

A device may generate neural network encryption models based on a dataset descriptor, a dataset geometry, and selected neural network types, and may generate obfuscation features based on the dataset descriptor, a noise type, an obfuscation model type, and noise and model parameters. The device may train the neural network encryption models, with a dataset and the obfuscation features, to generate model weights, a latent space, and noising and denoising models, and may generate an intelligent decryption model based on the model weights, the latent space, and the noising and denoising models. The device may receive an encrypted dataset associated with a target environment, and may determine whether the target environment is valid according to immune rules. The device may process, based on determining that the target environment is valid, the encrypted dataset, with the intelligent decryption model, to generate a decrypted dataset.