Author

Hanlin Zhang

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Open access Oct 2026

PA-CFL: Privacy-Preserving Adaptive Clustered Federated Learning Under Heterogeneous Data

Clustered federated learning (CFL) addresses data heterogeneity by grouping clients with similar data distributions and training personalized models for each cluster. However, existing CFL schemes depend on clustering-related parameters that require prior knowledge of client data distributions. Such information is ofte...

Tai-Hao Zhang, Wen-Ting Shen, Han-Lin Zhang et al. · Mathematics · 0 citations

Conference Jul 2026

VOLE-CPSI Meets Paillier Aggregation: Practical Private Intersection Cardinality with Linear-Scale Performance

Private set intersection (PSI) and its circuit variant (Circuit-PSI, CPSI) are core tools for privacy-preserving analytics. Unlike plain PSI that directly reveals intersecting elements, CPSI outputs secret shares of intersection indicators (and associated-value shares), which can be reused in subsequent MPC tasks witho...

Hai Zhang, Yi-Yun Guo, Li-Yan Shang et al. · International Conference on... · 0 citations

2026

MsaaDI: A Heterogeneity-Resilient Federated Learning Framework for IoT Device Identification With Multi-Scale Adaptive Aggregation

Accurate IoT device identification is critical to network forensics, access control, and anomaly detection in large-scale, security-sensitive environments. Federated learning (FL) provides a decentralized and privacy-enhancing approach well suited to IoT, but FL-based identification remains hampered by cross-client dat...

Tong Sun, Qian Lu, Hanlin Zhang et al. · IEEE Transactions on Informa... · 0 citations