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Showing 1 to 3 of 3 for “"Membership Inference"”.
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Data Centric Defenses for Privacy Attacks
… are implemented for two attacks namely membership inference and model inversion using two distinct techniques. While the proposed augmentations offer a better privacy-utility tradeoff on CIFAR-10 for membership inference, they reduce the reconstruction rate to ≤ 1% while reducing the …
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On Identifying and Mitigating Against Vulnerabilities of Machine Learning Models
… the privacy vulnerability of ML models using membership inference (MI) attacks to facilitate the design and training of privacy- preserving models. An MI attack is a fundamental attack that has been widely considered the simplest attack to evaluate the privacy of the training data of ML models …
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Privacy-Preserving Natural Language Dataset Generation
… has shown the ease with which attacks such as membership inference or model inversion can extract potentially sensitive training data given the model alone. To prevent curious or malevolent users from gleaning training data through these attacks, we propose the generation of private synthetic …