Incremental learning through reverse data distribution

A system having one or more computer processors, the system configured to:

• receive new data to be inputted into a previously trained machine learning model, wherein the previously trained machine learning model has inaccessible training data;
• generate simulated training data using a reverse form of the previously trained machine learning model;
• verify the simulated training data;
• create a new machine learning model using the simulated training data, wherein the new machine learning model comprises a same structure as the previously trained machine learning model;
• and
• input the new data into the new machine learning model, wherein the new machine learning model is further trained with the new data.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a server to cause the server to perform a method, the method comprising:

• receiving new data to be inputted into a previously trained machine learning model, wherein the previously trained machine learning model has inaccessible training data;
• generating simulated training data using a reverse form of the previously trained machine learning model;
• verifying the simulated training data;
• creating a new machine learning model using the simulated training data, wherein the new machine learning model comprises a same structure as the previously trained machine learning model;
• and
• inputting the new data into the new machine learning model, wherein the new machine learning model is further trained with the new data.