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Model Poisoning

Papers

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Showing 41–50 of 108 papers

TitleStatusHype
Federated Learning-Based Data Collaboration Method for Enhancing Edge Cloud AI System Security Using Large Language Models—0
Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing—0
ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning—0
FedRAD: Federated Robust Adaptive Distillation—0
FedRDF: A Robust and Dynamic Aggregation Function against Poisoning Attacks in Federated Learning—0
DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences—0
DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks—0
Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning (full version)—0
BaFFLe: Backdoor detection via Feedback-based Federated Learning—0
Mitigating Malicious Attacks in Federated Learning via Confidence-aware Defense—0
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