Bosen Rao

MultiKD: Backdoor Defense in Federated Graph Learning via Attention-Guided Multi-Teacher Distillation

Backdoor attacks pose a severe threat to federated graph learning (FGL), where malicious clients can inject hidden triggers into the global model without being detected. Defending against such attacks is particularly challenging due to the complex graph structures and the stealthy nature of trigger