Springer Nature OA
open access
CC BY 4.0
Federated deep learning for distributed intrusion detection and privacy preservation in power networks
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects#200897
- Deep Federated Learning-Based Privacy-Preserving Wind Power Forecasting#177293
- DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation#2472
- Advancing Power System Services With Privacy-Preserving Federated Learning Techniques: A Review#177263
- Privacy-preserving machine learning: a review of federated learning techniques and applications#964892
Record · ID 355768
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive