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Leveraging Label Information for Stealthy Data Stealing in Vertical Federated Learning
May 1, 2024, 4:42 a.m. | Duanyi Yao, Songze Li, Xueluan Gong, Sizai Hou, Gaoning Pan
cs.LG updates on arXiv.org arxiv.org
Abstract: We develop DMAVFL, a novel attack strategy that evades current detection mechanisms. The key idea is to integrate a discriminator with auxiliary classifier that takes a full advantage of the label information (which was completely ignored in previous attacks): on one hand, label information helps to better characterize embeddings of samples from distinct classes, yielding an improved reconstruction performance; on the other hand, computing malicious gradients with label information better mimics the honest training, making …
abstract arxiv attacks classifier cs.cr cs.lg current data detection federated learning information key novel stealing strategy the key type
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