diff --git a/tensorflow_privacy/privacy/membership_inference_attack/data_structures.py b/tensorflow_privacy/privacy/membership_inference_attack/data_structures.py
index fbafcd6..4e1acf3 100644
--- a/tensorflow_privacy/privacy/membership_inference_attack/data_structures.py
+++ b/tensorflow_privacy/privacy/membership_inference_attack/data_structures.py
@@ -114,11 +114,12 @@ class AttackType(enum.Enum):
   RANDOM_FOREST = 'rf'
   K_NEAREST_NEIGHBORS = 'knn'
   THRESHOLD_ATTACK = 'threshold'
+  THRESHOLD_ENTROPY_ATTACK = 'threshold-entropy'
 
   @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)
 
   def __str__(self):
     """Returns LOGISTIC_REGRESSION instead of AttackType.LOGISTIC_REGRESSION."""
diff --git a/tensorflow_privacy/privacy/membership_inference_attack/dataset_slicing.py b/tensorflow_privacy/privacy/membership_inference_attack/dataset_slicing.py
index 8e5e4b0..fe108a6 100644
--- a/tensorflow_privacy/privacy/membership_inference_attack/dataset_slicing.py
+++ b/tensorflow_privacy/privacy/membership_inference_attack/dataset_slicing.py
@@ -41,12 +41,14 @@ def _slice_data_by_indices(data: AttackInputData, idx_train,
   result.probs_train = _slice_if_not_none(data.probs_train, idx_train)
   result.labels_train = _slice_if_not_none(data.labels_train, idx_train)
   result.loss_train = _slice_if_not_none(data.loss_train, idx_train)
+  result.entropy_train = _slice_if_not_none(data.entropy_train, idx_train)
 
   # Slice test data.
   result.logits_test = _slice_if_not_none(data.logits_test, idx_test)
   result.probs_test = _slice_if_not_none(data.probs_test, idx_test)
   result.labels_test = _slice_if_not_none(data.labels_test, idx_test)
   result.loss_test = _slice_if_not_none(data.loss_test, idx_test)
+  result.entropy_test = _slice_if_not_none(data.entropy_test, idx_test)
 
   return result
 
diff --git a/tensorflow_privacy/privacy/membership_inference_attack/membership_inference_attack.py b/tensorflow_privacy/privacy/membership_inference_attack/membership_inference_attack.py
index 8f877a7..ae88464 100644
--- a/tensorflow_privacy/privacy/membership_inference_attack/membership_inference_attack.py
+++ b/tensorflow_privacy/privacy/membership_inference_attack/membership_inference_attack.py
@@ -96,6 +96,19 @@ def _run_threshold_attack(attack_input: AttackInputData):
       attack_type=AttackType.THRESHOLD_ATTACK,
       roc_curve=roc_curve)
 
+def _run_threshold_entropy_attack(attack_input: AttackInputData):
+  fpr, tpr, thresholds = metrics.roc_curve(
+      np.concatenate((np.zeros(attack_input.get_train_size()),
+                      np.ones(attack_input.get_test_size()))),
+      np.concatenate(
+          (attack_input.get_entropy_train(), attack_input.get_entropy_test())))
+
+  roc_curve = RocCurve(tpr=tpr, fpr=fpr, thresholds=thresholds)
+
+  return SingleAttackResult(
+      slice_spec=_get_slice_spec(attack_input),
+      attack_type=AttackType.THRESHOLD_ENTROPY_ATTACK,
+      roc_curve=roc_curve)
 
 def _run_attack(attack_input: AttackInputData,
                 attack_type: AttackType,
@@ -104,7 +117,8 @@ def _run_attack(attack_input: AttackInputData,
   if attack_type.is_trained_attack:
     return _run_trained_attack(attack_input, attack_type,
                                balance_attacker_training)
-
+  if attack_type == AttackType.THRESHOLD_ENTROPY_ATTACK:
+    return _run_threshold_entropy_attack(attack_input)
   return _run_threshold_attack(attack_input)