| Investigating Membership Inference Attacks under Data Dependencies | Oct 23, 2020 | BIG-bench Machine LearningInference Attack | CodeCode Available | 0 |
| Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated Learning | Nov 29, 2023 | Federated LearningInference Attack | CodeCode Available | 0 |
| An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models | Aug 17, 2022 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| An Empirical Study on the Intrinsic Privacy of SGD | Dec 5, 2019 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| Automatic Calibration for Membership Inference Attack on Large Language Models | May 6, 2025 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| On the privacy-utility trade-off in differentially private hierarchical text classification | Mar 4, 2021 | General ClassificationInference Attack | CodeCode Available | 0 |
| Assessing differentially private deep learning with Membership Inference | Dec 24, 2019 | Deep LearningInference Attack | CodeCode Available | 0 |
| Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software Deployment | Aug 11, 2022 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference | Feb 2, 2022 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning | Mar 30, 2022 | Federated LearningInference Attack | CodeCode Available | 0 |
