Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Krčo, Nataša, Guépin, Florent, Meeus, Matthieu, Kulynych, Bogdan, de Montjoye, Yves-Alexandre |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Sub-optimal Learning in Meta-Classifier Attacks: A Study of Membership Inference on Differentially Private Location Aggregates
por: Liu, Yuhan, et al.
Publicado: (2024)
por: Liu, Yuhan, et al.
Publicado: (2024)
RAT-Bench: A Comprehensive Benchmark for Text Anonymization
por: Krčo, Nataša, et al.
Publicado: (2026)
por: Krčo, Nataša, et al.
Publicado: (2026)
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
por: Guan, Vincent, et al.
Publicado: (2024)
por: Guan, Vincent, et al.
Publicado: (2024)
The Tail Tells All: Estimating Model-Level Membership Inference Vulnerability Without Reference Models
por: Dodd, Euodia, et al.
Publicado: (2025)
por: Dodd, Euodia, et al.
Publicado: (2025)
Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data
por: Guépin, Florent, et al.
Publicado: (2023)
por: Guépin, Florent, et al.
Publicado: (2023)
Achilles' Heels: Vulnerable Record Identification in Synthetic Data Publishing
por: Meeus, Matthieu, et al.
Publicado: (2023)
por: Meeus, Matthieu, et al.
Publicado: (2023)
Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
por: Meeus, Matthieu, et al.
Publicado: (2023)
por: Meeus, Matthieu, et al.
Publicado: (2023)
SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)
por: Meeus, Matthieu, et al.
Publicado: (2024)
por: Meeus, Matthieu, et al.
Publicado: (2024)
Correlation inference attacks against machine learning models
por: Creţu, Ana-Maria, et al.
Publicado: (2021)
por: Creţu, Ana-Maria, et al.
Publicado: (2021)
The DCR Delusion: Measuring the Privacy Risk of Synthetic Data
por: Yao, Zexi, et al.
Publicado: (2025)
por: Yao, Zexi, et al.
Publicado: (2025)
Checkpoint-GCG: Auditing and Attacking Fine-Tuning-Based Prompt Injection Defenses
por: Yang, Xiaoxue, et al.
Publicado: (2025)
por: Yang, Xiaoxue, et al.
Publicado: (2025)
Copyright Traps for Large Language Models
por: Meeus, Matthieu, et al.
Publicado: (2024)
por: Meeus, Matthieu, et al.
Publicado: (2024)
DeSIA: Attribute Inference Attacks Against Limited Fixed Aggregate Statistics
por: Mao, Yifeng, et al.
Publicado: (2025)
por: Mao, Yifeng, et al.
Publicado: (2025)
QueryCheetah: Fast Automated Discovery of Attribute Inference Attacks Against Query-Based Systems
por: Stevanoski, Bozhidar, et al.
Publicado: (2024)
por: Stevanoski, Bozhidar, et al.
Publicado: (2024)
Counterfactual Influence as a Distributional Quantity
por: Meeus, Matthieu, et al.
Publicado: (2025)
por: Meeus, Matthieu, et al.
Publicado: (2025)
Membership Inference Attacks Against In-Context Learning
por: Wen, Rui, et al.
Publicado: (2024)
por: Wen, Rui, et al.
Publicado: (2024)
Secure Aggregation is Not Private Against Membership Inference Attacks
por: Ngo, Khac-Hoang, et al.
Publicado: (2024)
por: Ngo, Khac-Hoang, et al.
Publicado: (2024)
Investigating the Effect of Misalignment on Membership Privacy in the White-box Setting
por: Cretu, Ana-Maria, et al.
Publicado: (2023)
por: Cretu, Ana-Maria, et al.
Publicado: (2023)
Rethinking Membership Inference Attacks Against Transfer Learning
por: Wu, Cong, et al.
Publicado: (2025)
por: Wu, Cong, et al.
Publicado: (2025)
Re-pseudonymization Strategies for Smart Meter Data Are Not Robust to Deep Learning Profiling Attacks
por: Cretu, Ana-Maria, et al.
Publicado: (2024)
por: Cretu, Ana-Maria, et al.
Publicado: (2024)
Evaluating the Defense Potential of Machine Unlearning against Membership Inference Attacks
por: Tsiolakis, Theodoros, et al.
Publicado: (2025)
por: Tsiolakis, Theodoros, et al.
Publicado: (2025)
Bayes-Nash Generative Privacy Against Membership Inference Attacks
por: Zhang, Tao, et al.
Publicado: (2024)
por: Zhang, Tao, et al.
Publicado: (2024)
Membership Inference Attacks Against Video Large Language Models
por: Song, Wei, et al.
Publicado: (2026)
por: Song, Wei, et al.
Publicado: (2026)
Lost in Modality: Evaluating the Effectiveness of Text-Based Membership Inference Attacks on Large Multimodal Models
por: Tong, Ziyi, et al.
Publicado: (2025)
por: Tong, Ziyi, et al.
Publicado: (2025)
Neighborhood Blending: A Lightweight Inference-Time Defense Against Membership Inference Attacks
por: Zafar, Osama, et al.
Publicado: (2026)
por: Zafar, Osama, et al.
Publicado: (2026)
Membership Inference Attacks Against Vision-Language Models
por: Hu, Yuke, et al.
Publicado: (2025)
por: Hu, Yuke, et al.
Publicado: (2025)
Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models
por: Chen, Zeyuan, et al.
Publicado: (2026)
por: Chen, Zeyuan, et al.
Publicado: (2026)
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
por: Li, Jiacheng, et al.
Publicado: (2023)
por: Li, Jiacheng, et al.
Publicado: (2023)
Ensembling Membership Inference Attacks Against Tabular Generative Models
por: Ward, Joshua, et al.
Publicado: (2025)
por: Ward, Joshua, et al.
Publicado: (2025)
Center-Based Relaxed Learning Against Membership Inference Attacks
por: Fang, Xingli, et al.
Publicado: (2024)
por: Fang, Xingli, et al.
Publicado: (2024)
Practical Bayes-Optimal Membership Inference Attacks
por: Lassila, Marcus, et al.
Publicado: (2025)
por: Lassila, Marcus, et al.
Publicado: (2025)
Membership Inference Attacks and Defenses in Federated Learning: A Survey
por: Bai, Li, et al.
Publicado: (2024)
por: Bai, Li, et al.
Publicado: (2024)
Membership Inference Attack Against Masked Image Modeling
por: Li, Zheng, et al.
Publicado: (2024)
por: Li, Zheng, et al.
Publicado: (2024)
Free Record-Level Privacy Risk Evaluation Through Artifact-Based Methods
por: Pollock, Joseph, et al.
Publicado: (2024)
por: Pollock, Joseph, et al.
Publicado: (2024)
Imitative Membership Inference Attack
por: Du, Yuntao, et al.
Publicado: (2025)
por: Du, Yuntao, et al.
Publicado: (2025)
Improved Membership Inference Attacks Against Language Classification Models
por: Shachor, Shlomit, et al.
Publicado: (2023)
por: Shachor, Shlomit, et al.
Publicado: (2023)
Membership Inference Attacks on Vision-Language-Action Models
por: Peng, Yuefeng, et al.
Publicado: (2026)
por: Peng, Yuefeng, et al.
Publicado: (2026)
A Data-Free Membership Inference Attack on Federated Learning in Hardware Assurance
por: Lee, Gijung, et al.
Publicado: (2026)
por: Lee, Gijung, et al.
Publicado: (2026)
When Reasoning Leaks Membership: Membership Inference Attack on Black-box Large Reasoning Models
por: Hu, Ruihan, et al.
Publicado: (2026)
por: Hu, Ruihan, et al.
Publicado: (2026)
Membership Inference Attacks on Sequence Models
por: Rossi, Lorenzo, et al.
Publicado: (2025)
por: Rossi, Lorenzo, et al.
Publicado: (2025)
Ejemplares similares
-
Sub-optimal Learning in Meta-Classifier Attacks: A Study of Membership Inference on Differentially Private Location Aggregates
por: Liu, Yuhan, et al.
Publicado: (2024) -
RAT-Bench: A Comprehensive Benchmark for Text Anonymization
por: Krčo, Nataša, et al.
Publicado: (2026) -
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data
por: Guan, Vincent, et al.
Publicado: (2024) -
The Tail Tells All: Estimating Model-Level Membership Inference Vulnerability Without Reference Models
por: Dodd, Euodia, et al.
Publicado: (2025) -
Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data
por: Guépin, Florent, et al.
Publicado: (2023)