| Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM Alignment | Jul 8, 2024 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Federated Graph Condensation with Information Bottleneck Principles | May 7, 2024 | Graph LearningInference Attack | —Unverified | 0 |
| Low-Cost Privacy-Preserving Decentralized Learning | Mar 18, 2024 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Label-Only Membership Inference Attack against Node-Level Graph Neural Networks | Jul 27, 2022 | Graph ClassificationInference Attack | —Unverified | 0 |
| A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis | Jan 18, 2022 | Domain AdaptationInference Attack | —Unverified | 0 |
| Low-Cost High-Power Membership Inference Attacks | Dec 6, 2023 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Differentially Private Data Generative Models | Dec 6, 2018 | BIG-bench Machine LearningFederated Learning | —Unverified | 0 |
| Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation | Jan 18, 2024 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| A Federated Parameter Aggregation Method for Node Classification Tasks with Different Graph Network Structures | Mar 24, 2024 | Federated LearningGraph Neural Network | —Unverified | 0 |
| De-identification is not always enough | Jan 31, 2024 | De-identificationInference Attack | —Unverified | 0 |
