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cs.IT2026
Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning
Hengxuan Tang, Jinbao Zhu, Xiaohu Tang
Secure aggregation is a vital component for mitigating gradient leakage in federated learning, but its communication cost conventionally scales with the gradient dimension. This be…
cs.IT2026
The Capacity of Information-Theoretic Secure Aggregation in Federated Learning
Lanxin Yi, Jinbao Zhu, Kai Wan +1
Secure aggregation allows a server to aggregate users' local updates while preserving update privacy. Existing information-theoretic problems typically assume that correlated rando…
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…