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Membership Inference Attack

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Showing 101–150 of 186 papers

TitleStatusHype
Differentially Private and Adversarially Robust Machine Learning: An Empirical Evaluation—0
Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software DeploymentCode0
Task Contamination: Language Models May Not Be Few-Shot Anymore—0
Low-Cost High-Power Membership Inference AttacksCode0
DUCK: Distance-based Unlearning via Centroid KinematicsCode0
Privacy and Accuracy Implications of Model Complexity and Integration in Heterogeneous Federated LearningCode0
MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated LearningCode0
Are Normalizing Flows the Key to Unlocking the Exponential Mechanism?Code0
Preserving Privacy in GANs Against Membership Inference Attack—0
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative ModelsCode0
Black-Box Training Data Identification in GANs via Detector Networks—0
A Comprehensive Study of Privacy Risks in Curriculum Learning—0
SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition SystemsCode0
A Probabilistic Fluctuation based Membership Inference Attack for Diffusion ModelsCode0
Epsilon*: Privacy Metric for Machine Learning Models—0
Membership Inference Attacks on DNNs using Adversarial PerturbationsCode0
Towards More Realistic Membership Inference Attacks on Large Diffusion Models—0
Set-Membership Inference Attacks using Data Watermarking—0
Membership inference attack with relative decision boundary distance—0
Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?—0
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models—0
Do Backdoors Assist Membership Inference Attacks?—0
Membership Inference Attack for Beluga Whales Discrimination—0
Targeted Attack on GPT-Neo for the SATML Language Model Data Extraction Challenge—0
Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes—0
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models—0
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds—0
Interaction-level Membership Inference Attack Against Federated Recommender Systems—0
Holistic risk assessment of inference attacks in machine learning—0
Privacy-Preserving Collaborative Learning through Feature Extraction—0
Purifier: Defending Data Inference Attacks via Transforming Confidence Scores—0
Privacy in Practice: Private COVID-19 Detection in X-Ray Images (Extended Version)Code0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
Privacy Attacks Against Biometric Models with Fewer Samples: Incorporating the Output of Multiple Models—0
An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis ModelsCode0
Safety and Performance, Why not Both? Bi-Objective Optimized Model Compression toward AI Software DeploymentCode0
On the Evaluation of User Privacy in Deep Neural Networks using Timing Side Channel—0
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks—0
White-box Membership Attack Against Machine Learning Based Retinopathy Classification—0
A Blessing of Dimensionality in Membership Inference through Regularization—0
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated LearningCode0
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation—0
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks—0
User-Level Membership Inference Attack against Metric Embedding Learning—0
An Efficient Subpopulation-based Membership Inference Attack—0
LTU Attacker for Membership InferenceCode0
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership InferenceCode0
A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis—0
DP-UTIL: Comprehensive Utility Analysis of Differential Privacy in Machine LearningCode0
Machine unlearning via GAN—0
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