An Understanding of the Vulnerability of Datasets to Disparate Membership Inference Attacks
Recent efforts have shown that training data is not secured through the generalization and abstraction of algorithms. This vulnerability to the training data has been expressed through membership inference attacks that seek to discover the use of specific records within the training dataset of a mod...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2022-12-01
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| Colección: | Journal of Cybersecurity and Privacy |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/2624-800X/2/4/45 |
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