Yong Xiang

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...