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Inference Attack
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective
Apollo: A Posteriori Label-Only Membership Inference Attack Towards Machine Unlearning
When Better Features Mean Greater Risks: The Performance-Privacy Trade-Off in Contrastive Learning
Membership Inference Attacks on Sequence Models
An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression
Securing Genomic Data Against Inference Attacks in Federated Learning Environments
AugMixCloak: A Defense against Membership Inference Attacks via Image Transformation
Automatic Calibration for Membership Inference Attack on Large Language Models
A new membership inference attack that spots memorization in generative and predictive models: Loss-Based with Reference Model algorithm (LBRM)
Whispers of Data: Unveiling Label Distributions in Federated Learning Through Virtual Client Simulation
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
Disparate Privacy Vulnerability: Targeted Attribute Inference Attacks and Defenses
Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks
BLIA: Detect model memorization in binary classification model through passive Label Inference attack
DP-GPL: Differentially Private Graph Prompt Learning
Efficient Membership Inference Attacks by Bayesian Neural Network
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
Membership Inference Attacks for Face Images Against Fine-Tuned Latent Diffusion Models
A hierarchical approach for assessing the vulnerability of tree-based classification models to membership inference attack
Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
Privacy Attacks on Image AutoRegressive Models
Tool Unlearning for Tool-Augmented LLMs
Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks
Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach
Differentially Private Steering for Large Language Model Alignment
Membership Inference Attacks Against Vision-Language Models
Unlearning Clients, Features and Samples in Vertical Federated Learning
Technical Report for the Forgotten-by-Design Project: Targeted Obfuscation for Machine Learning
Tag&Tab: Pretraining Data Detection in Large Language Models Using Keyword-Based Membership Inference Attack
A Volumetric Approach to Privacy of Dynamical Systems
From Models to Network Topologies: A Topology Inference Attack in Decentralized Federated Learning
AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation
Prompt-based Unifying Inference Attack on Graph Neural Networks
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