Dec 4, 2023 · In this paper, we introduce a technique, weighted smoothing (WS), to mitigate MIA risks. Our approach is anchored on the observation that ...
Dec 4, 2023 · In this paper, we introduce a technique, weighted smoothing (WS), to mitigate MIA risks. Our approach is anchored on the observation that ...
Dec 4, 2023 · In this work, we focus on MIA mitigation approaches that add perturbation to the training phase. We introduce a method termed weighted smoothing ...
By training a shadow model to mimic the target model's inference, and then using the data generated by the shadow model to train the attack model.
In this paper, we introduce a technique, weighted smoothing (WS), to mitigate MIA risks. Our approach is anchored on the observation that training samples ...
This technique selectively introduces noise to training samples, considering their class distribution, effectively mitigating MIA risks while preserving model ...
To mitigate MIAs in different forms, we observe that they can be unified as they all exploit the ML model's overconfidence in predicting training samples.
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A curated list of membership inference attacks and defenses papers on machine learning models. Papers are sorted by their released dates in descending order.
Jul 2, 2024 · We train each model with 200 epochs using the SGD optimizer with a weight decay of 5e-4 and momentum of 0.9. We set the initial learning ...
Jun 1, 2024 · In this paper, we provide the first systematic study to assess the effectiveness of differential privacy for protecting collaborative inference ...