via “privacy-preserving-defense-mechanisms”
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) i
Unique: Provides integrated FedMLDefender component with pluggable defense strategies (differential privacy, robust aggregation, anomaly detection) that apply transparently to any federated learning algorithm without code modification, combined with FedMLAttacker for adversarial testing
More comprehensive defense suite than TensorFlow Federated (which focuses on DP) and includes attack simulation framework for validation; tighter integration with federated learning pipeline than standalone privacy libraries