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Marco Di Gennaro
@marcodige.bsky.social

🚨 Our PoPETS 2025 work, "TimberStrike," finds that federated tree models are vulnerable to privacy leakage via dataset reconstruction. See you in Washington D.C. in July! 📄 Preprint: www.arxiv.org/abs/2506.07605 #FederatedLearning #Privacy #PoPETS

arxiv.orgTimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based SystemsFederated Learning has emerged as a privacy-oriented alternative to centralized Machine Learning, enabling collaborative model training without direct data sharing. While extensively studied for neura...
Marco Di Gennaro
@marcodige.bsky.social

We found that federated tree-based models (like XGBoost) are vulnerable to dataset reconstruction attacks, and we demonstrated this vulnerability across major FL frameworks. Our work introduces a novel attack and provides guidelines for building stronger defenses.

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