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Tutorial

1. Federated Learning
2. Model Inversion
3. Label Leakage
- 3.1. Split Learning and Label Leakage
4. Membership Inference
- 4.1. Memership Inference
5. Poisoning Attack
- 5.1. Poisoning Attack against Federated Learning
- 5.2. Poisoning Attack against SVM
6. Backdoor Attack
- 6.1. Backdoor Attack against Federated Learning
7. Evasion Attack
8. Differential Privacy
9. K-anonymity
- 9.1. K-anonymity
10. Debugging
- 10.1. Neuron Coverage
- 10.2. Model Assertions
11. Homomorphic Encryption
- 11.1. Paillier Encryption

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By Hideaki Takahashi