Semantic Scholar
metadata only
Efficient Verifiable Protocol for Privacy-Preserving Aggregation in Federated Learning
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
- TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning#341905
- Privacy-Preserving Federated Learning Using Homomorphic Encryption#177306
- Privacy-Preserving Big Data Security for IoT With Federated Learning and Cryptography#177308
- Efficient Privacy-Preserving Federated Learning with Sensitivity-Based Selective Homomorphic Encryption#431809
- No More Guessing: a Verifiable Gradient Inversion Attack in Federated Learning#18949
Record · ID 177285
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