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diff --git a/synthetic/conclusion.tex b/synthetic/conclusion.tex new file mode 100644 index 0000000..bb6dd17 --- /dev/null +++ b/synthetic/conclusion.tex @@ -0,0 +1,6 @@ +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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