Security & Privacy

Membership Inference Attacks Against Time-Series Models ACML 2024 Membership Inference Attack Using Self Influence Functions WACV 2024 Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy NeurIPS 2024 Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract COLT 2024 Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor NeurIPS 2024 Mitigating Privacy Seesaw in Large Language Models: Augmented Privacy Neuron Editing via Activation Patching ACL 2024 Mixing Gradients in Neural Networks as a Strategy To Enhance Privacy in Federated Learning WACV 2024 Model Inversion Robustness: Can Transfer Learning Help? CVPR 2024 Multi-Dimensional Fair Federated Learning AAAI 2024 MultiLeg: Dataset for Text Sanitisation in Less-resourced Languages COLING 2024 NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations WACV 2024 Neural Codec-based Adversarial Sample Detection for Speaker Verification Interspeech 2024 Noise-Aware Differentially Private Regression via Meta-Learning NeurIPS 2024 Noisy Dual Mirror Descent: A Near Optimal Algorithm for Jointly-DP Convex Resource Allocation NeurIPS 2024 Noisy Neighbors: Efficient membership inference attacks against LLMs ACL 2024 On Convex Optimization with Semi-Sensitive Features COLT 2024 On Differentially Private Federated Linear Contextual Bandits ICLR 2024 On Differentially Private Subspace Estimation in a Distribution-Free Setting NeurIPS 2024 On Differentially Private U Statistics NeurIPS 2024 One-shot Empirical Privacy Estimation for Federated Learning ICLR 2024 Online Distribution Learning with Local Privacy Constraints AISTATS 2024 Online Sensitivity Optimization in Differentially Private Learning AAAI 2024 On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint) IJCAI 2024 On provable privacy vulnerabilities of graph representations NeurIPS 2024 On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NeurIPS 2024