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Membership Inference Attack

Papers

Showing 2650 of 186 papers

TitleStatusHype
Membership Inference Attacks From First PrinciplesCode1
An Efficient Membership Inference Attack for the Diffusion Model by Proximal InitializationCode1
Membership Inference Attacks on Machine Learning: A SurveyCode1
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial ExamplesCode1
Membership Inference Attack Using Self Influence FunctionsCode1
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning ModelsCode1
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy RiskCode1
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning ModelsCode1
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device MLCode1
Membership Inference Attacks against Large Vision-Language ModelsCode1
Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference PerspectiveCode0
Automatic Calibration for Membership Inference Attack on Large Language ModelsCode0
MIA-BAD: An Approach for Enhancing Membership Inference Attack and its Mitigation with Federated LearningCode0
A Method to Facilitate Membership Inference Attacks in Deep Learning ModelsCode0
Membership Inference Attacks on DNNs using Adversarial PerturbationsCode0
Assessing differentially private deep learning with Membership InferenceCode0
DocMIA: Document-Level Membership Inference Attacks against DocVQA ModelsCode0
Membership Inference Attacks on Lottery Ticket NetworksCode0
A Probabilistic Fluctuation based Membership Inference Attack for Diffusion ModelsCode0
Differentially Private Steering for Large Language Model AlignmentCode0
Investigating Membership Inference Attacks under Data DependenciesCode0
Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity RecognitionCode0
LTU Attacker for Membership InferenceCode0
Apollo: A Posteriori Label-Only Membership Inference Attack Towards Machine UnlearningCode0
Generated Distributions Are All You Need for Membership Inference Attacks Against Generative ModelsCode0
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