A deep network's intermediate layers can be ranked by privacy risk using estimated degrees of freedom and Jacobian rank, which the authors link to membership inference attack success.
Privacy risk in machine learning: Analyzing the connection to overfitting
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Intermediate Outputs Are More Sensitive Than You Think
A deep network's intermediate layers can be ranked by privacy risk using estimated degrees of freedom and Jacobian rank, which the authors link to membership inference attack success.