Disparate Vulnerability to Membership Inference Attacks
A membership inference attack (MIA) against a machine-learning model enables an attacker to determine whether a given data record was part of the model’s training data or not. In this paper, we provide an in-depth study of the phenomenon of disparate vulnerability against MIAs: unequal success rate...
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Autores principales: | Kulynych Bogdan, Yaghini Mohammad, Cherubin Giovanni, Veale Michael, Troncoso Carmela |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Sciendo
2022
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Materias: | |
Acceso en línea: | https://doaj.org/article/c3bf6102ce1b4060b1996827dc5cbec5 |
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