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About LOGAN - Membership Inference Attacks
1) The document discusses membership inference attacks against generative models. These attacks aim to determine if a given data point was used to train the generative model. 2) The attacks are presented for both white-box and black-box settings against several state-of-the-art generative models using complex datasets. 3) The white-box attacks are shown to be 100% successful at inferring training data. Black-box attacks using GANs are able to recover over 80% of the training set in some cases.
Detailed Information
| Author: | ['MessyAnd InStyle'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 20 |
| Language: | English |
| Format: | |
| Price: | FREE |
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