Intuit Inc.
FEATURE RANDOMIZATION FOR SECURING MACHINE LEARNING MODELS
Last updated:
Abstract:
Feature randomization for securing machine learning models includes receiving an event, and altering, responsive to receiving the event, a threshold pseudo-randomly to generate an altered threshold value. Feature randomization further includes applying the altered threshold value to a threshold-dependent feature to generate an altered threshold-dependent feature value. The altered threshold-dependent feature value determined at least in part from the event. Feature randomization further includes executing a machine learning model, on the event and the altered threshold-dependent feature value, to generate a predicted event type for the event.
Status:
Application
Type:
Utility
Filling date:
27 Jan 2021
Issue date:
28 Jul 2022