← Application Areas
Machine Learning › Application Areas ›

Privacy

2794 directly classified papers

Papers per year

Papers

PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds IJCAI 2024
EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection AAAI 2024
LR-XFL: Logical Reasoning-Based Explainable Federated Learning AAAI 2024
Federated Partial Label Learning with Local-Adaptive Augmentation and Regularization AAAI 2024
Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains IJCAI 2024
Chronic Poisoning: Backdoor Attack against Split Learning AAAI 2024
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach NIPS 2024
Protecting Object Detection Models from Model Extraction Attack via Feature Space Coverage IJCAI 2024
Does Few-Shot Learning Suffer from Backdoor Attacks? AAAI 2024
GS-Hider: Hiding Messages into 3D Gaussian Splatting NIPS 2024
Flock: A Framework for Deploying On-Demand Distributed Trust OSDI 2024
Locally Differentially Private In-Context Learning COLING 2024
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees AAAI 2024
HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning NIPS 2024
Continual Counting with Gradual Privacy Expiration NIPS 2024
Differentially Private Knowledge Distillation via Synthetic Text Generation ACL 2024
Practical Privacy-Preserving MLaaS: When Compressive Sensing Meets Generative Networks AAAI 2024
A Privacy-preserving Approach to Ingest Knowledge from Proprietary Web-based to Locally Run Models for Medical Progress Note Generation ACL 2024
IPRemover: A Generative Model Inversion Attack against Deep Neural Network Fingerprinting and Watermarking AAAI 2024
On the Robustness of Neural-Enhanced Video Streaming against Adversarial Attacks AAAI 2024
MuST: Robust Image Watermarking for Multi-Source Tracing AAAI 2024
Confidence Is All You Need for MI Attacks (Student Abstract) AAAI 2024
Once and for All: Universal Transferable Adversarial Perturbation against Deep Hashing-Based Facial Image Retrieval AAAI 2024
Data-Free Hard-Label Robustness Stealing Attack AAAI 2024
Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data NIPS 2024