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When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers through Membership Inference Attacks
It leverages the difference in the predictions from both the original and fairness-enhanced models and exploits the observed prediction gaps as attack clues.
How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
As a booming research area in the past decade, deep learning technologies have been driven by big data collected and processed on an unprecedented scale.
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