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Trusted FL (Federated Learning)
SGX-based End-to-end Trusted FL platform
ID & Feature align
Before we start Federated Learning, we need to align ID & Feature, and figure out portions of local data that will participate in later training stage.
Let RID1 and RID2 be randomized ID from party 1 and party 2.
Vertical FL
Vertical FL training across multi-parties with different features.
Key features:
- FL Server in SGX
- ID & feature align
- Forward & backward aggregation
- Training node in SGX
Horizontal FL
Horizontal FL training across multi-parties.
Key features:
- FL Server in SGX
- ID & feature align (optional)
- Weight/Gradient Aggregation in SGX
- Training Worker in SGX
References
- Intel SGX
- Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2019. Federated Machine Learning: Concept and Applications. ACM Trans. Intell. Syst. Technol. 10, 2, Article 12 (February 2019), 19 pages. DOI:https://doi.org/10.1145/3298981