US 2024/0202322 A1 · EFFICIENT PROTOTYPING OF ADVERSARIAL ATTACKS AND DEFENSES ON TRANSFER LEARNING SETTINGS

Abstract

Techniques are disclosed for providing a framework for fast prototyping attacks and defenses on transfer learning settings. For example, a system can include at least one processing device including a processor coupled to a memory, the at least one processing device being configured to perform the following steps: defining a set of evaluation metrics, each evaluation metric configured to test responses by a machine learning model when applying a given defense among a set of defenses against a set of adversarial inputs generated for the model; selecting one or more defenses from the set of defenses based on the evaluation metrics; and generating a secured model based on incorporating the selected defenses into the model.

Claims20

Dependent claims

A system comprising:

at least one processing device including a processor coupled to a memory;
the at least one processing device being configured to implement the following steps:
defining a set of evaluation metrics, each evaluation metric configured to test responses by a machine learning model when applying a given defense among a set of defenses against a set of adversarial inputs generated for the model;
selecting one or more defenses from the set of defenses based on the evaluation metrics;
and
generating a secured model based on incorporating the selected defenses into the model.

3 more elements

Dependencies are inferred from the claim text.

Efficient prototyping of adversarial attacks and defenses on transfer learning settings

Life of this patent

Efficient prototyping of adversarial attacks and defenses on transfer learning settings

Life of this patent

Abstract

Claims20