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Classroom Contents
Comprehensive Privacy Analysis of Deep Learning
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- 1 Intro
- 2 Deep learning Tasks
- 3 Privacy Threats
- 4 Membership Inference
- 5 Training a Model
- 6 Gradients Leak Information
- 7 Different Learning/Attack Settings
- 8 Active Attack on Federated Learning
- 9 Active Attacks in Federated Model
- 10 Fully Trained Model
- 11 Central Attacker in Federated Model
- 12 Local Attacker in Federated Learning
- 13 Score function
- 14 Experimental Setup
- 15 Pretrained Models Attacks
- 16 Federated Attacks
- 17 Conclusions
