[HTML][HTML] A survey on membership inference attacks and defenses in Machine Learning
Membership inference (MI) attacks mainly aim to infer whether a data record was used to
train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a …
train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a …
Towards principled assessment of tabular data synthesis algorithms
Y Du, N Li - arXiv preprint arXiv:2402.06806, 2024 - arxiv.org
Data synthesis has been advocated as an important approach for utilizing data while
protecting data privacy. A large number of tabular data synthesis algorithms (which we call …
protecting data privacy. A large number of tabular data synthesis algorithms (which we call …
SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks
G Amit, A Goldsteen, A Farkash - arXiv preprint arXiv:2403.08481, 2024 - arxiv.org
Natural language processing models have experienced a significant upsurge in recent
years, with numerous applications being built upon them. Many of these applications require …
years, with numerous applications being built upon them. Many of these applications require …
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
AM Cretu, D Jones, YA de Montjoye, S Tople - arXiv preprint arXiv …, 2023 - arxiv.org
Machine learning models have been shown to leak sensitive information about their training
datasets. Models are increasingly deployed on devices, raising concerns that white-box …
datasets. Models are increasingly deployed on devices, raising concerns that white-box …