Bank of America Corporation
DISTRIBUTED ARTIFICIAL INTELLIGENCE MODEL WITH DECEPTION NODES

Abstract:

A model designer improves the security of a machine learning model in certain embodiments. Instead of storing the model in a central location, the training data used to build and train the model is stored across several different databases and/or datacenters. The training data is divided into portions and stored as a circular linked list across these databases and/or datacenters. The model designer retrieves the training data and incrementally builds and trains the model using the training data. The incremental error and bias of the model is used to locate training data between datacenters. Additionally, fake training data is appended to the circular linked list and the model designer tracks how much training data is used before hitting fake training data.