Security & Privacy

On the Computational Complexity of Private High-dimensional Model Selection NeurIPS 2024 On the sample complexity of privately learning half-spaces ACML 2024 Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives NeurIPS 2024 Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? COLT 2024 Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Order of Magnitude Speedups for LLM Membership Inference EMNLP 2024 OSLO: One-Shot Label-Only Membership Inference Attacks NeurIPS 2024 PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining NeurIPS 2024 PII-Compass: Guiding LLM training data extraction prompts towards the target PII via grounding ACL 2024 Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding AAAI 2024 PostMark: A Robust Blackbox Watermark for Large Language Models EMNLP 2024 PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning AAAI 2024 Practical Privacy-Preserving MLaaS: When Compressive Sensing Meets Generative Networks AAAI 2024 Preset-Voice Matching for Privacy Regulated Speech-to-Speech Translation Systems ACL 2024 Pre-training Differentially Private Models with Limited Public Data NeurIPS 2024 Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy NeurIPS 2024 PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024 Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions AAAI 2024 Privacy Amplification for Matrix Mechanisms ICLR 2024 Privacy-Aware Randomized Quantization via Linear Programming UAI 2024 Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models NeurIPS 2024 Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients AISTATS 2024 Privacy-Enhancing Person Re-Identification Framework - A Dual-Stage Approach WACV 2024 Privacy-Preserving Face Recognition Using Trainable Feature Subtraction CVPR 2024