arXiv · 2306.00133
A Note On Interpreting Canary Exposure
Abstract
Canary exposure, introduced in Carlini et al. is frequently used to empirically evaluate, or audit, the privacy of machine learning model training. The goal of this note is to provide some intuition on how to interpret canary exposure, including by relating it to membership inference attacks and differential privacy.
Explore related subjects
Keep this discovery
Matthew Jagielski. 2023-05-31. A Note On Interpreting Canary Exposure. https://arxiv.org/abs/2306.00133
Cite the original work for its findings. Save a collection to share your selection of sources.