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Tutorial
1. Federated Learning
1.1. FedAVG
1.2. FedAVG with Paillier Encryption
1.3. FedAVG with Sparse Gradient
1.4. FedMD: Federated Learning with Model Distillation
1.5. SecureBoost: Vertically Federated XGBoost with Paillier Encryption
2. Model Inversion
2.1. MI-FACE
2.2. Gradient-based Model Inversion Attack against Federated Learning
2.3. GAN Attack
2.4. Soteria: : Provable Defense against Privacy Leakage in Federated Learning g from Representation Perspective
2.5. Mutual Information-based Defense
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
7.1. Evasion Attack against SVM
7.2. DIVA
7.3. Exploring Adversarial Example Transferability and Robust Tree Models
7.4. PixelDP
8. Differential Privacy
8.1. Differential Privacy and Moment Accountant
8.2. MI-FACE vs DPSGD
8.3. AdaDPS
8.4. DPlis
9. K-anonymity
9.1. K-anonymity
10. Debugging
10.1. Neuron Coverage
10.2. Model Assertions
11. Homomorphic Encryption
11.1. Paillier Encryption
API Docs
1. aijack.attack package
1.1.1. aijack.attack.backdoor package
1.1.2. aijack.attack.evasion package
1.1.3. aijack.attack.freerider package
1.1.4. aijack.attack.inversion package
1.1.4.1.1. aijack.attack.inversion.utils package
1.1.5. aijack.attack.labelleakage package
1.1.6. aijack.attack.membership package
1.1.7. aijack.attack.poison package
2. aijack.defense package
2.1.1. aijack.defense.crobustness package
2.1.2. aijack.defense.debugging package
2.1.2.1.1. aijack.defense.debugging.assertions package
2.1.2.1.2. aijack.defense.debugging.neuroncoverage package
2.1.3. aijack.defense.dp package
2.1.3.1.1. aijack.defense.dp.manager package
2.1.4. aijack.defense.foolsgold package
2.1.5. aijack.defense.kanonymity package
2.1.6. aijack.defense.mid package
2.1.7. aijack.defense.paillier package
2.1.8. aijack.defense.soteria package
2.1.9. aijack.defense.sparse package
3. aijack.collaborative package
3.1.1. aijack.collaborative.core package
3.1.2. aijack.collaborative.dsfl package
3.1.3. aijack.collaborative.fedavg package
3.1.4. aijack.collaborative.fedexp package
3.1.5. aijack.collaborative.fedgems package
3.1.6. aijack.collaborative.fedkd package
3.1.7. aijack.collaborative.fedmd package
3.1.8. aijack.collaborative.fedprox package
3.1.9. aijack.collaborative.moon package
3.1.10. aijack.collaborative.optimizer package
3.1.11. aijack.collaborative.splitnn package
3.1.12. aijack.collaborative.tree package
4. aijack.utils package
Developer Docs
1. Contribution Guide
.rst
.pdf
Backdoor Attack
6.
Backdoor Attack
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6.1. Backdoor Attack against Federated Learning
