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cs.CR2026
Repurposing Backdoors for Good: Ephemeral Intrinsic Proofs for Verifiable Aggregation in Cross-silo Federated Learning
Xian Qin, Xue Yang, Xiaohu Tang
While Secure Aggregation (SA) protects update confidentiality in Cross-silo Federated Learning, it fails to guarantee aggregation integrity, allowing malicious servers to silently…
cs.CR2025
Efficient Byzantine-Robust Privacy-Preserving Federated Learning via Dimension Compression
Xian Qin, Xue Yang, Xiaohu Tang
Federated Learning (FL) allows collaborative model training across distributed clients without sharing raw data, thus preserving privacy. However, the system remains vulnerable to…