most citedTask-Agnostic Privacy-Preserving Representation Learning for Federated Learning Against Attribute Inference Attacks

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cs.LG2024

Learning Robust and Privacy-Preserving Representations via Information Theory

Binghui Zhang, Sayedeh Leila Noorbakhsh, Yun Dong +2

Machine learning models are vulnerable to both security attacks (e.g., adversarial examples) and privacy attacks (e.g., private attribute inference). We take the first step to miti…

cs.LG2024

Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks

Sayedeh Leila Noorbakhsh, Binghui Zhang, Yuan Hong +1

Machine learning (ML) is vulnerable to inference (e.g., membership inference, property inference, and data reconstruction) attacks that aim to infer the private information of trai…