Citadel is a scalable collaborative ML system that protects the privacy of both data owner and model owner in untrusted infrastructures . Citadel performs distributed training across multiple training enclaves running on behalf of data owners and an aggregatorenclave . Citadel scales to alarge number of enclaves with less than 1.73X slowdown caused by SGX . Citadel establishes a stronginformation barrier between these enclaves by means of zero-sum masking and Hierarchical aggregation to prevent data/model leakage during collaborativetraining . Compared with the existing SGX-protected training systems, Citadelenables better scalability and stronger privacy guarantees for collaborativeML. Compared with existing . ML-protected-training systems , Citadel enables better scalabilities and stronger security guarantees for the collaborativeML . It is available to download from for $99.99/, or download from $100, or $99/GBGB/GB/ For more information, visit .

Author(s) : Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan

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Keywords : citadel - training - data - model - sgx -

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