Add threshold-entropy attack #131
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CdavM
suggested changes
Oct 23, 2020
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| @property | ||
| def is_trained_attack(self): | ||
| """Returns whether this type of attack requires training a model.""" | ||
| return self != AttackType.THRESHOLD_ATTACK | ||
| return (self != AttackType.THRESHOLD_ATTACK) & (self != AttackType.THRESHOLD_ENTROPY_ATTACK) |
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Can we use words instead, i.e. self != AttackType.THRESHOLD_ATTACK and self != AttackType.THRESHOLD_ENTROPY_ATTACK
| @@ -96,6 +96,19 @@ def _run_threshold_attack(attack_input: AttackInputData): | |||
| attack_type=AttackType.THRESHOLD_ATTACK, | |||
| roc_curve=roc_curve) | |||
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| def _run_threshold_entropy_attack(attack_input: AttackInputData): | |||
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Can we add an end-to-end test for this to membership_inference_attack_test.py? Something like the "test_run_attack_threshold_calculates_correct_auc" test
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The test case is added!
I have fixed these issues, please take another look, thanks. |
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Following our recent paper https://arxiv.org/pdf/2003.10595.pdf, I implement the code to run membership inference attacks by setting a threshold value on the prediction entropy value.
Compared to THRESHOLD_ATTACK, THRESHOLD_ENTROPY_ATTACK leverages the entropy value instead of the loss value.