Author

M. M. Hassan

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Open access 2026

FedShield: Configurable Mean–Median Robust Aggregation for Poisoning-Resilient Federated Healthcare-IoT Learning

Federated learning lets healthcare-IoT and Internet of Medical Things (IoMT) systems train shared models without centralizing sensitive records, but poisoned client updates can degrade the global model, and the Byzantine-robust aggregators meant to prevent this behave unevenly across the non-IID data partitions these d...

A. Alajaji, Maryam Jamal Alablani, M. M. Hassan · IEEE Access · 0 citations

Open access 2026

Feature-Space Adversarial Robustness Evaluation of Lightweight ML-Based Intrusion Detection for IoT and Healthcare-Sensing Networks

Machine learning (ML)-based Network Intrusion Detection Systems (NIDS) are increasingly deployed in IoT and healthcare-sensing networks. Reported robustness depends on how it is measured: evaluations relying on attacks transferred from a surrogate cannot separate a robust decision boundary from a merely dissimilar one,...

A. Alajaji, Rawan Alharbi, M. M. Hassan et al. · IEEE Access · 0 citations

Sep 2026

An explainable deep learning approach for automated detection and grading of diabetic retinopathy from fundus images.

Diabetic Retinopathy (DR) is a leading cause of preventable blindness, and it is important to accurately detect it as early as possible, as well as to measure the severity to provide early clinical indicators. Fundus image assessment in the manual mode is subjective and labor-intensive, and is hard to scale, which has...

Muradul Islam, Marisa Parvez Oishy, Ferdaus Anam Jibon et al. · Microvascular Research · 0 citations