opake-auditing
Empirical privacy auditing for Opake: one-run estimator (Steinke et al. 2023), coin-flip canary partitioning, and loss-based membership-inference attacks.
Install
Install the root package as described in the repository installation guide.
Use its auditing extra to include this component.
opake-auditing depends on opake-engine and scipy; both install
automatically with the extra.
Quick start
import opake.auditing as auditing
from opake.random import key
cf = auditing.coin_flip(dataset, num_canaries=1000, key=key(42))
# ... DP-SGD training loop ...
estimate = auditing.one_run(scores, coin_flip=cf)
By default, canaries are sampled from the dataset's natural rows. Pass
candidate_indices= to restrict selection to a precommitted pool of constructed
or selected records.
Layout
opake.auditing.one_run— one-run estimator (Steinke et al. 2023)opake.auditing.coin_flip()— coin-flip canary partitioningopake.auditing.loss_scores()— loss-based membership inference viavmap
1 maintainer
Metadata
1 maintainer
Release files for opake-auditing 0.16.0
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