Yongfeng Huang
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The paper proposes M extsuperscript{3}Att, a knowledge-poisoning framework that injects covert misinformation into medical multimodal RAG systems using paired visual data triggers, demonstrating attacks that generate clinically plausible but incorrect diagnoses.
EnCAgg proposes a novel robust aggregation method for federated learning that uses reference clients and advanced clustering techniques to accurately filter dynamic model poisoning attacks while minimizing the loss of benign client gradients.
Papers
EnCAgg: Enhanced Clustering Aggregation for Robust Federated Learning against Dynamic Model Poisoning
Tianyun Zhang, Zhen Yang, Haozhao Wang, Ru Zhang +1 more
EnCAgg proposes a novel robust aggregation method for federated learning that uses reference clients and advanced clustering techniques to accurately filter dynamic model poisoning attacks while minim…