Patent ID: 11886955
Assignee: PROTOPIA AI, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising:
obtaining, by a computer system, a training dataset;
training, with the computer system, one or more machine learning models as an autoencoder to generate as output a reconstruction of a record in the training dataset based on an input of the record in the training dataset, wherein the autoencoder comprises at least one deterministic layer and wherein training is based on optimization of a value indicative of reconstruction loss and wherein the record is multi-dimensional;
adding, with the computer system, one or more stochastic noise layers to the trained one or more machine learning models of the autoencoder,
wherein the one or more stochastic noise layers are additional layers among the layers of the trained one or more machine learning models of the autoencoder,
wherein each of the stochastic noise layers inject noise by, for each of at least a plurality of dimensions of the stochastic noise layer, sampling from a parametric noise distribution for respective dimensions, and adding for each stochastic noise layer, noise to an encoded representation of a record at the respective stochastic noise layer, and
wherein the parametric noise distributions for each of the at least the plurality of dimensions are independent;

adjusting, with the computer system, parameters of the parametric noise distributions for the dimensions of the one or more stochastic noise layers according to an objective function that is differentiable, wherein the objective function comprises a measure of adversarial loss;
storing, with the computer system, the one or more machine learning models of the autoencoder with the stochastic noise layers in memory;
obtaining, by the computer system, one or more records from a second dataset;
generating, with the stored one or more machine learning models of the autoencoder with the stochastic noise layers, one or more obfuscated records for the one or more records from the second dataset; and
transmitting, by the computer system, the one or more obfuscated records by an untrusted network.