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Titlebook: Computer Security – ESORICS 2024; 29th European Sympos Joaquin Garcia-Alfaro,Rafał Kozik,Sokratis Katsika Conference proceedings 2024 The E

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Lecture Notes in Computer Sciencef FedAvgCKA across various federated learning scenarios and datasets, showcasing its ability to maintain high main task accuracy and significantly reduce backdoor attack success rates even in non-iid settings.
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VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purificationuently, VFLIP conducts purification which removes the embeddings identified as malicious and reconstructs all the embeddings based on the remaining embeddings. We conduct extensive experiments on CIFAR10, CINIC10, Imagenette, NUS-WIDE, and Bank-Marketing to demonstrate that VFLIP can effectively mitigate backdoor attacks in VFL.
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