Can this work be federated？

[njuptlht]

I read your another work "federated xgboost", which stated that it does not support differential privacy. If I implement this work in a distributed system, can it be considered federated？

[chester-leung]

Hi @njuptlht thanks for your interest in our project.

The Secure XGBoost model is that of multiparty outsourced computation, i.e. where all parties' data are individually encrypted and entirely transferred to a central cluster for processing. This is different from federated learning, in which only data summaries are exchanged between parties and a central aggregator service, and in which (in its vanilla form) summaries are unencrypted. The XGBoost training algorithm, however, natively exchange summaries -- see section 3 of the paper here for more.

If you are looking for differential privacy, this project also does not yet support it.