A Knowledge Distillation-Based Backdoor Attack in Federated Learning. (arXiv:2208.06176v1 [cs.LG])

Federated Learning (FL) is a novel framework of decentralized machine
learning. Due to the decentralized feature of FL, it is vulnerable to
adversarial attacks in the training procedure, e.g. , backdoor attacks. A
backdoor attack aims to inject a backdoor into the machine learning model such
that the model will make arbitrarily incorrect behavior on the test sample with
some specific backdoor trigger. Even though a range of backdoor attack methods
of FL has been introduced, there are also methods …

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