الباحثون

Y. Thomas Hou

المنشورات 2

نسخة أولية وصول مفتوح

Aegis: Generative Gradient Masking for Privacy-Preserving Medical Federated Learning

Chaoyu Zhang, Shanghao Shi, Heng Jin وآخرون · 2026

Federated learning (FL) has become a foundational paradigm for multi-institutional medical AI, allowing hospitals and research centers to jointly train diagnostic models without exchanging patient records. This privacy promise, however, is increasingly contested: a malicious or honest-but-curious server can launch mode …

نسخة أولية وصول مفتوح

zkSAS: Practical Zero-Knowledge Proofs for Verifiable Spectrum Access Management

Nishat F. Purbasha, Ifteher Alom, Eric W. Burger وآخرون · 2026 · 10.1109/dyspan69846.2026.11571163

Dynamic Spectrum Access (DSA) through the Spectrum Access Systems (SAS) elevates spectral efficiency, yet existing centralized models face allocation logic opaqueness and a lack of independent verifiability. While blockchain-based SAS architectures offer transparency and verifiability by default, they introduce critica …

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