def test_run_attack_threshold_entropy_calculates_correct_auc(self):
result = mia._run_attack(
AttackInputData(
entropy_train=np.array([0.1, 0.2, 1.3, 0.4, 0.5, 0.6]),
entropy_test=np.array([1.1, 1.2, 1.3, 0.4, 1.5, 1.6])),
AttackType.THRESHOLD_ENTROPY_ATTACK)
np.testing.assert_almost_equal(result.roc_curve.get_auc(), 0.83, decimal=2)
def test_run_attack_threshold_entropy_sets_attack_type(self):
result = mia._run_attack(
get_test_input(100, 100), AttackType.THRESHOLD_ENTROPY_ATTACK)
self.assertEqual(result.attack_type, AttackType.THRESHOLD_ENTROPY_ATTACK)
def test_run_attack_threshold_entropy_sets_membership_scores(self):
result = mia._run_attack(
get_test_input(100, 50), AttackType.THRESHOLD_ENTROPY_ATTACK)
self.assertLen(result.membership_scores_train, 100)
self.assertLen(result.membership_scores_test, 50)
def test_run_attack_trained_sets_attack_type(self):
result = mia._run_attack(
get_test_input(100, 100), AttackType.LOGISTIC_REGRESSION)
self.assertEqual(result.attack_type, AttackType.LOGISTIC_REGRESSION)
