Cover Image

FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mahyar, Abtin, Shafieinejad, Masoumeh, Liu, Yuhan, He, Xi
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Cryptography and Security Databases
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Ensembling Membership Inference Attacks Against Tabular Generative Models
by: Ward, Joshua, et al.
Published: (2025)

TabularMark: Watermarking Tabular Datasets for Machine Learning
by: Zheng, Yihao, et al.
Published: (2024)

Systematic Assessment of Tabular Data Synthesis
by: Du, Yuntao, et al.
Published: (2024)

Adopt a PET! An Exploration of PETs, Policy, and Practicalities for Industry in Canada
by: Shafieinejad, Masoumeh, et al.
Published: (2025)

Rethinking Membership Inference Attacks Against Transfer Learning
by: Wu, Cong, et al.
Published: (2025)

Winning the MIDST Challenge: New Membership Inference Attacks on Diffusion Models for Tabular Data Synthesis
by: Wu, Xiaoyu, et al.
Published: (2025)

Membership Inference over Diffusion-models-based Synthetic Tabular Data
by: Cheng, Peini, et al.
Published: (2025)

Learning from Anonymized and Incomplete Tabular Data
by: Lange, Lucas, et al.
Published: (2026)

SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models
by: Shankar, Aditya, et al.
Published: (2024)

Differentially Private Synthetic Data Generation for Relational Databases
by: Alimohammadi, Kaveh, et al.
Published: (2024)

MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
by: Li, Jiacheng, et al.
Published: (2023)

Secure Aggregation is Not Private Against Membership Inference Attacks
by: Ngo, Khac-Hoang, et al.
Published: (2024)

FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
by: Zhu, Gongxi, et al.
Published: (2024)

ResidualPlanner+: a scalable matrix mechanism for marginals and beyond
by: Xiao, Yingtai, et al.
Published: (2023)

Improved Membership Inference Attacks Against Language Classification Models
by: Shachor, Shlomit, et al.
Published: (2023)

Enhancing Data Provenance and Model Transparency in Federated Learning Systems -- A Database Approach
by: Gu, Michael, et al.
Published: (2024)

MongoDB Injection Query Classification Model using MongoDB Log files as Training Data
by: Perni, Shaunak, et al.
Published: (2026)

Membership Inference Attacks on Sequence Models
by: Rossi, Lorenzo, et al.
Published: (2025)

Noise as a Probe: Membership Inference Attacks on Diffusion Models Leveraging Initial Noise
by: Lian, Puwei, et al.
Published: (2026)

Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective
by: Lian, Puwei, et al.
Published: (2025)

Lost in the Averages: A New Specific Setup to Evaluate Membership Inference Attacks Against Machine Learning Models
by: Krčo, Nataša, et al.
Published: (2024)

MINES: Explainable Anomaly Detection through Web API Invariant Inference
by: Zhang, Wenjie, et al.
Published: (2025)

Imitative Membership Inference Attack
by: Du, Yuntao, et al.
Published: (2025)

Center-Based Relaxed Learning Against Membership Inference Attacks
by: Fang, Xingli, et al.
Published: (2024)

DPSQL+: A Differentially Private SQL Library with a Minimum Frequency Rule
by: Matsumoto, Tomoya, et al.
Published: (2026)

PE-means: Improved Differentially Private $k$-means Clustering through Private Evolution
by: Humphries, Thomas, et al.
Published: (2026)

VeriX-Anon: A Multi-Layered Framework for Mathematically Verifiable Outsourced Target-Driven Data Anonymization
by: Daga, Miit, et al.
Published: (2026)

Privacy-Preserved Neural Graph Databases
by: Hu, Qi, et al.
Published: (2023)

Leveraging large language models for SQL behavior-based database intrusion detection
by: Shlezinger, Meital, et al.
Published: (2025)

Supersonic OT: Fast Unconditionally Secure Oblivious Transfer
by: Abadi, Aydin, et al.
Published: (2024)

CryptoTrain: Fast Secure Training on Encrypted Dataset
by: Xue, Jiaqi, et al.
Published: (2024)

Multi-Layer Privacy-Preserving Record Linkage with Clerical Review based on gradual information disclosure
by: Rohde, Florens, et al.
Published: (2024)

Differentially Private Selection using Smooth Sensitivity
by: Chaves, Iago, et al.
Published: (2025)

Differentially Private Learned Indexes
by: Du, Jianzhang, et al.
Published: (2024)

Preventing the Popular Item Embedding Based Attack in Federated Recommendations
by: Zhang, Jun, et al.
Published: (2025)

Towards Split Learning-based Privacy-Preserving Record Linkage
by: Zervas, Michail, et al.
Published: (2024)

Low-Cost High-Power Membership Inference Attacks
by: Zarifzadeh, Sajjad, et al.
Published: (2023)

Membership Inference Attacks for Unseen Classes
by: Thaker, Pratiksha, et al.
Published: (2025)

Membership Inference Attacks Beyond Overfitting
by: Khalil, Mona, et al.
Published: (2025)

Cascading and Proxy Membership Inference Attacks
by: Du, Yuntao, et al.
Published: (2025)