6G • Core Network
On-Device Federated Learning Client
Privacy-Preserving Decentralized AI Training Engine on 6G Terminals
Client runtime training AI models on local user data and transmitting only encrypted gradient updates to 6G edge servers.
Technical Explanation
To train cutting-edge foundation models without violating user privacy (GDPR/HIPAA), the 6G terminal runs an on-device federated learning client. The phone computes local model gradient updates on its NPU using the user's private on-device photos, typing patterns, and voice logs. It applies differential privacy noise and homomorphic encryption to the gradients before uploading them to the 6G core aggregator, ensuring raw private data never leaves the handset.
Key Functions
- Trains neural models locally on private user data inside secure hardware enclaves
- Applies differential privacy noise to prevent model inversion attacks
- Transmits compact encrypted gradient updates over 6G high-speed uplink
- Participates in collaborative global AI training across millions of edge devices
Specifications
ITU-T Y.3172 (ML in Future Networks), 3GPP TR 22.874 AI/ML Services
Interfaces
Local NPU TrainerEdge FL Aggregation GatewayDifferential Privacy Engine
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