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Guo-Hong Cao

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Conference Sep 2026

Exploiting Feature Non-IIDness for Untargeted Data Poisoning Attacks in Byzantine-Robust Federated Learning

This paper identifies and exploits feature non-IIDness, demonstrating that by manipulating only the features of local data on compromised clients, adversaries can generate malicious updates to bypass RA rules and significantly degrade the global model’s performance.

Jun-Zhe Huang, Chong-Qi Guan, Guo-Hong Cao · 0 citations

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