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A curated list of resources for model inversion attack (MIA).
### What is the model inversion attack?
In model inversion attacks, a malicious user attempts to recover the private dataset used to train a supervised neural network. A successful model inversion attack should generate realistic and diverse samples that accurately describe each of the classes in the private dataset.
(by Variational Model Inversion Attacks, Wang et al, 2021.)
The goal of model inversion attacks is to recreate training data or sensitive attributes.
(Chen et al, 2021.)
In model inversion attacks, a malicious user attempts to recover the private dataset used to train a supervised neural network. A successful model inversion attack should generate realistic and diverse samples that accurately describe each of the classes in the private dataset. (Wang et al, 2021.)
### Survey
Arxiv 2021 - A Survey of Privacy Attacks in Machine Learning.