Author

M. Hasan

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2026

Unmasking Composite Adversaries: A New Threat Model for Federated Learning

Federated learning (FL) is increasingly adopted in distributed and privacy-preserving applications for decentralized intelligence, yet it remains highly vulnerable to adversarial attacks. Existing defenses remain fundamentally limited to single-attack scenarios, which overlook the real-world risk of coordinated, multiv...

M. Hasan, Yong Xiang, Md. Palash Uddin et al. · IEEE Transactions on Reliabi... · 0 citations

Jul 2026

Asteroids, algorithms, and explainability: a unified framework for efficient classification of near-Earth objects

A robust, interpretable, and physically consistent DL framework for reliable asteroid orbit classification in planetary defense applications is established using attention-driven Deep Learning and explainable techniques.

Md Readion Islam Razon, Md Amir Hamja, Md. Tanjim et al. · Experimental astronomy (Prin... · 0 citations