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Leveraging Label Information for Stealthy Data Stealing in Vertical Federated Learning
We develop DMAVFL, a novel attack strategy that evades current detection mechanisms.
Secure Federated Clustering
We consider a foundational unsupervised learning task of $k$-means data clustering, in a federated learning (FL) setting consisting of a central server and many distributed clients.
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