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Let's Focus: Focused Backdoor Attack against Federated Transfer Learning
May 1, 2024, 4:11 a.m. | Marco Arazzi, Stefanos Koffas, Antonino Nocera, Stjepan Picek
cs.CR updates on arXiv.org arxiv.org
Abstract: Federated Transfer Learning (FTL) is the most general variation of Federated Learning. According to this distributed paradigm, a feature learning pre-step is commonly carried out by only one party, typically the server, on publicly shared data. After that, the Federated Learning phase takes place to train a classifier collaboratively using the learned feature extractor. Each involved client contributes by locally training only the classification layers on a private training set. The peculiarity of an FTL …
arxiv attack backdoor backdoor attack cs.cr cs.lg data distributed feature federated federated learning focus general paradigm party server train transfer
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