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Mei-Bin Qi

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Conference Sep 2026

A privacy protection method for large-scale graph data supported by homomorphic encryption

Given the characteristics of large-scale graph data, such as high-dimensional sparsity, topological coupling perturbations, and inherent heterogeneity in sensitive contexts, traditional coarse-grained privacy identification rules are unable to characterize these non-orthogonal semantic features. This leads to technical...

Mei-Bin Qi · 0 citations
#federated learning Conference Sep 2026

Robust detection method for adversarial backdoor attacks under federated learning architecture

Under federated learning, single-threshold norm verification cannot effectively distinguish malicious from benign updates with similar norms, resulting in low detection robustness. This paper proposes a robust detection method featuring a two layer "norm verification + directional consistency" filtering mechanism combi...

Mei-Bin Qi · 0 citations

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