Machine-learning apparatus and technique

A method of operating a privacy-aware model-based machine learning engine comprising:

• receiving a data request from an open model-based machine learning engine to initiate data capture;
• responsive to receiving the data request, capturing data comprising sensitive and non-sensitive data to a first dataset;
• scanning the first dataset to detect the sensitive data;
• responsive to detecting the sensitive data, creating an obscured representation of the sensitive data to be stored with the non-sensitive data in a second dataset;
• and
• delivering the second dataset to the open model-based machine learning engine.

A computer program product stored on a non-transitory computer-readable medium and comprising computer program code to, when loaded into a computer system and executed thereon, cause the computer system to:

• receive a data request from an open model-based machine learning engine to initiate data capture;
• responsive to receiving the data request, capture data comprising sensitive and non-sensitive data to a first dataset;
• scan the first dataset to detect the sensitive data;
• responsive to detecting the sensitive data, create an obscured representation of the sensitive data to be stored with the non-sensitive data in a second dataset;
• and
• deliver the second dataset to the open model-based machine learning engine.