Extracting Cloud-based Model with Prior Knowledge

Understand

Machine Learning-as-a-Service, a pay-as-you-go business pattern, is widely accepted by third-party users and developers.

• However, the open inference APIs may be utilized by malicious customers to conduct model extraction attacks, i.e., attackers can replicate a cloud-based black-box model merely via querying malicious examples.
• Existing model extraction attacks mainly depend on the posterior knowledge (i.e., predictions of query samples) from Oracle.
• Thus, they either require high query overhead to simulate the decision boundary, or suffer from generalization errors and overfitting problems due to query budget limitations.