Machine learning (ml) model pipeline with obfuscation to protect sensitive data therein

Abstract

Provided is a system and platform for Machine Learning (ML) based Data Discovery and Classification. The system and platform comprising components of a user console, a ML agent, and a ML data engine. By way of a ML pipeline, sensitive data is obfuscated that would otherwise by in the clear when transmitted to a centralized server. The ML model pipeline decouples embedding from model training. In a first step, the ML Agent runs on data endpoint machine or proxy to convert clear text data to embedding vectors. In a second step, the ML data engine runs on a centralized server to train models using the embedding vectors. The separation of pipeline components and respective handling of workflow requests and messages associated therewith prevents the transfer of clear data in the open. Other embodiments disclosed.