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+Even though synthetic dataset are promising regarding users' data protection, in itself it does not bring guaranties regarding attribute inference attack.
+For future work we suggest that applying fairness regularization during the training of the generator could be a way to remove bias toward sensitive attributes.
+
+Concerning membership inference attack, synthetic data reduce the overall risk while still leaving an attack surface on some outliers points.
+Differential privacy is a way to reduce the risk on outliers but removing entirely the risk while keeping some level of utility is impossible. 
+Hence more work in this direction is required.
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