blob: e8969c248e905c625e8849c8494ee80a3bdf622d (
plain)
1
2
3
4
5
6
7
8
9
|
\subsection{Research questions}
\label{sec:question}
%\textbf{What is the impact of using synthetic data instead of real data on users' privacy when training machine learning models?}
\textbf{How does using synthetic data instead of real data affect users' privacy in the context of training machine learning models?}
User's privacy and neural network clash at two levels: membership inference and attribute inference.
Membership inference refers to the possibility of infering weather or not a data record belongs to the training data.
Attribute inference refers to how a trained model can be leveraged to infer a sensitive attribute such as the race or the gender.
|
