Comments (3)
Hi @xjc1234567 ,
The attacks S and P are incorporated in the shadow_metric and population_metric function respectively in the privacy meter (see here). To get more details of how these attacks are executed, please consult the files shadow_metric.ipynb and population_metric.ipynb.
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Thank you for your answer, but I have one more question here. I did not find the training details of the target model for attack S,P,R,D such as hyperparameters because the paper provided at the conference did not include appendix. arXiv provided the paper with the training details but the data is quite different from the conference version. Can you provide me more training details about the target model to reproduce your attack?
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Related Issues (20)
- Question regarding ussage of ModelIntermediateOutput class in information_source_signal.py HOT 1
- Time HOT 1
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- Pytorch implementation HOT 2
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- Can't exploit gradients of ResNet-20 HOT 4
- can i attack linear regression、logistic、XGBoost
- can i attack linear regression、logistic、XGBoost models? HOT 1
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- Code of "MIA via Distillation" HOT 1
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- Old tutorials with restructured code HOT 1
- Add conda recipe HOT 8
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