Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting

Understand

Machine learning models have been shown to leak sensitive information about their training datasets.

• Models are increasingly deployed on devices, raising concerns that white-box access to the model parameters increases the attack surface compared to black-box access which only provides query access.
• Directly extending the shadow modelling technique from the black-box to the white-box setting has been shown, in general, not to perform better than black-box only attacks.
• A potential reason is misalignment, a known characteristic of deep neural networks.