| Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation | Jan 18, 2024 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment | Jan 2, 2024 | Inference AttackMembership Inference Attack | CodeCode Available | 0 |
| Task Contamination: Language Models May Not Be Few-Shot Anymore | Dec 26, 2023 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Low-Cost High-Power Membership Inference Attacks | Dec 6, 2023 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| DUCK: Distance-based Unlearning via Centroid Kinematics | Dec 4, 2023 | Inference AttackMachine Unlearning | 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 |
| MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated Learning | Nov 28, 2023 | Federated LearningInference Attack | CodeCode Available | 0 |
| Are Normalizing Flows the Key to Unlocking the Exponential Mechanism? | Nov 15, 2023 | Bayesian InferenceInference Attack | CodeCode Available | 0 |
| Preserving Privacy in GANs Against Membership Inference Attack | Nov 6, 2023 | Inference AttackMembership Inference Attack | —Unverified | 0 |
| Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models | Oct 30, 2023 | AllInference Attack | CodeCode Available | 0 |
