Author

Jing-Sha He

2 papers indexed here

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#federated learning Oct 2026

FedDCDS: a dual-phase secure federated learning framework with dynamic clustering and adaptive delivery

FedDCDS introduces a novel dual-phase secure federated learning framework designed to address the intertwined challenges of statistical heterogeneity, system heterogeneity, and security threats in large-scale edge computing environments. By integrating a dynamic spectral clustering mechanism, the framework dynamically...

Li-Yuan Zhang, Na-Fei Zhu, Jing-Sha He et al. · Cluster Computing · 0 citations

#edge computing Review Open access Sep 2026

Editorial: Artificial Intelligence-Driven Information Security and Privacy Enhancement Technologies

Artificial intelligence-driven methods have the potential to improve malicious code detection, vulnerability discovery, fuzz testing, network attack detection, cryptographic computation, zero-knowledge verification, and privacy-preserving distributed learning for increasingly complex digital environments.

Jing-Sha He, Dragan Peraković, B. Ray · Journal of universal compute... · 0 citations