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Privacy

363 directly classified papers

Papers per year

Papers

Minimax Optimal Two-Sample Testing under Local Differential Privacy JMLR 2025
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning AAAI 2025
Investigating How Pre-training Data Leakage Affects Models’ Reproduction and Detection Capabilities EMNLP 2025
A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks AAAI 2025
Differential Privacy Mechanisms in Neural Tangent Kernel Regression WACV 2025
Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing CVPR 2025
Exploring Query Efficient Data Generation Towards Data-Free Model Stealing in Hard Label Setting AAAI 2025
On Probabilistic Truncation in Privacy-preserving Machine Learning AAAI 2025
Differentially Private Fine-Tuning of Diffusion Models ICCV 2025
CDI: Copyrighted Data Identification in Diffusion Models CVPR 2025
Where Does This Data Come From? Enhanced Source Inference Attacks in Federated Learning IJCAI 2025
Privacy-and-Utility-Aware Publishing of Schedules AAAI 2025
Watermarking Large Language Models: An Unbiased and Low-risk Method ACL 2025
Stealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack ACL 2025
Reminiscence Attack on Residuals: Exploiting Approximate Machine Unlearning for Privacy ICCV 2025
Gradient Coreset for Federated Learning WACV 2024
Learn To Unlearn for Deep Neural Networks: Minimizing Unlearning Interference With Gradient Projection WACV 2024
Towards More Realistic Membership Inference Attacks on Large Diffusion Models WACV 2024
$\texttt{pfl-research}$: simulation framework for accelerating research in Private Federated Learning NIPS 2024
Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024
Analysis of Differentially Private Synthetic Data: A Measurement Error Approach AAAI 2024
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy AAAI 2024
Blind-Touch: Homomorphic Encryption-Based Distributed Neural Network Inference for Privacy-Preserving Fingerprint Authentication AAAI 2024
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach NIPS 2024
The Relative Gaussian Mechanism and its Application to Private Gradient Descent AISTATS 2024