Privacy preservation of data over a shared network

Abstract

System and method are disclosed for preserving privacy of shared data over a shared network. A vector encoder transforms received data into a feature vector. An autoencoder includes a neural network-based encoder transforms the feature vector into a fixed size latent space representation of the received data. A neural network-based decoder of the autoencoder is configured to reconstruct the feature vector from the latent space representation. The autoencoder is trained using training data with an objective to minimize reconstruction error. A vector decoder transforms the reconstructed feature vector into reconstructed data. The latent space representation of data from the trained autoencoder is shared as anonymized data with at least one trusted party over the shared network, decoded offline using a replica of the trained decoder.