US 12,348,619 B2
Systems and methods for providing enhanced multi-layered security with encryption models that improve zero-trust architectures
Said Soulhi, Saint Cloud, FL (US); and Adam Barron, Leesburg, VA (US)
Assigned to Verizon Patent and Licensing Inc., Basking Ridge, NJ (US)
Filed by Verizon Patent and Licensing Inc., Basking Ridge, NJ (US)
Filed on May 15, 2023, as Appl. No. 18/317,476.
Prior Publication US 2024/0388423 A1, Nov. 21, 2024
Int. Cl. H04L 9/08 (2006.01); G06N 3/08 (2023.01)
CPC H04L 9/0847 (2013.01) [G06N 3/08 (2013.01); H04L 9/0869 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
generating, by a device, neural network encryption models based on a dataset descriptor, a dataset geometry, and selected neural network types;
generating, by the device, obfuscation features based on the dataset descriptor, a noise type, an obfuscation model type, and noise and model parameters;
training, by the device, the neural network encryption models, with a dataset and the obfuscation features, to generate model weights, a latent space, and noising and denoising models;
generating, by the device, an intelligent decryption model based on the model weights, the latent space, and the noising and denoising models;
receiving, by the device, an encrypted dataset associated with a target environment;
processing, by the device, the encrypted dataset, with the intelligent decryption model, to determine whether the target environment is valid according to immune rules; and
selectively:
preventing, by the device, decryption of the encrypted dataset based on determining that the target environment is invalid, or
processing, by the device and based on determining that the target environment is valid, the encrypted dataset, with the intelligent decryption model, to generate a decrypted dataset.