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Inference Attack

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TitleStatusHype
Quality Inference in Federated Learning with Secure Aggregation—0
Tool Unlearning for Tool-Augmented LLMs—0
Towards Black-Box Membership Inference Attack for Diffusion Models—0
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models—0
Towards More Realistic Membership Inference Attacks on Large Diffusion Models—0
Towards Reliable Empirical Machine Unlearning Evaluation: A Game-Theoretic View—0
Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models—0
On the Impact of Uncertainty and Calibration on Likelihood-Ratio Membership Inference Attacks—0
Impact of Dataset Properties on Membership Inference Vulnerability of Deep Transfer Learning—0
Unlearning Clients, Features and Samples in Vertical Federated Learning—0
Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation—0
Unveiling Privacy Vulnerabilities: Investigating the Role of Structure in Graph Data—0
Unveiling Structural Memorization: Structural Membership Inference Attack for Text-to-Image Diffusion Models—0
Unveiling Synthetic Faces: How Synthetic Datasets Can Expose Real Identities—0
User-Level Membership Inference Attack against Metric Embedding Learning—0
VertexSerum: Poisoning Graph Neural Networks for Link Inference—0
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles—0
Membership Inference Attacks Against Temporally Correlated Data in Deep Reinforcement Learning—0
Whispers of Data: Unveiling Label Distributions in Federated Learning Through Virtual Client Simulation—0
White-box Inference Attacks against Centralized Machine Learning and Federated Learning—0
White-box Membership Attack Against Machine Learning Based Retinopathy Classification—0
Machine Unlearning for Uplink Interference Cancellation—0
Machine unlearning via GAN—0
Many-Shot Regurgitation (MSR) Prompting—0
Against Membership Inference Attack: Pruning is All You Need—0
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