Copertina

Membership Inference Attacks on Sequence Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Rossi, Lorenzo, Aerni, Michael, Zhang, Jie, Tramèr, Florian
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Cryptography and Security Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Evaluations of Machine Learning Privacy Defenses are Misleading
di: Aerni, Michael, et al.
Pubblicazione: (2024)

Blind Baselines Beat Membership Inference Attacks for Foundation Models
di: Das, Debeshee, et al.
Pubblicazione: (2024)

Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
di: Zhang, Jie, et al.
Pubblicazione: (2024)

Large-scale online deanonymization with LLMs
di: Lermen, Simon, et al.
Pubblicazione: (2026)

Imitative Membership Inference Attack
di: Du, Yuntao, et al.
Pubblicazione: (2025)

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

Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
di: Feng, Shanglun, et al.
Pubblicazione: (2024)

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

Membership Inference Attacks Beyond Overfitting
di: Khalil, Mona, et al.
Pubblicazione: (2025)

Membership Inference Attacks on Large-Scale Models: A Survey
di: Wu, Hengyu, et al.
Pubblicazione: (2025)

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

Membership Inference Attacks and Privacy in Topic Modeling
di: Manzonelli, Nico, et al.
Pubblicazione: (2024)

Practical Bayes-Optimal Membership Inference Attacks
di: Lassila, Marcus, et al.
Pubblicazione: (2025)

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
di: Debenedetti, Edoardo, et al.
Pubblicazione: (2024)

SeqMIA: Sequential-Metric Based Membership Inference Attack
di: Li, Hao, et al.
Pubblicazione: (2024)

Adversarial ML Problems Are Getting Harder to Solve and to Evaluate
di: Rando, Javier, et al.
Pubblicazione: (2025)

Laundering AI Authority with Adversarial Examples
di: Zhang, Jie, et al.
Pubblicazione: (2026)

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

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

MRMMIA: Membership Inference Attacks on Memory in Chat Agents
di: Chen, Kai, et al.
Pubblicazione: (2026)

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

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

On Membership Inference Attacks in Knowledge Distillation
di: Cui, Ziyao, et al.
Pubblicazione: (2025)

Adversarial Search Engine Optimization for Large Language Models
di: Nestaas, Fredrik, et al.
Pubblicazione: (2024)

Evaluating Membership Inference Attacks in heterogeneous-data setups
di: van Dartel, Bram, et al.
Pubblicazione: (2025)

Sequential Membership Inference Attacks
di: Michel, Thomas, et al.
Pubblicazione: (2026)

Membership Inference Attack with Partial Features
di: Wang, Xurun, et al.
Pubblicazione: (2025)

Empirical Comparison of Membership Inference Attacks in Deep Transfer Learning
di: Bai, Yuxuan, et al.
Pubblicazione: (2025)

OSLO: One-Shot Label-Only Membership Inference Attacks
di: Peng, Yuefeng, et al.
Pubblicazione: (2024)

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning
di: Chen, Depeng, et al.
Pubblicazione: (2024)

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

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

ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks
di: Huang, Chihan, et al.
Pubblicazione: (2026)

SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks
di: Amit, Guy, et al.
Pubblicazione: (2024)

Modal Aphasia: Can Unified Multimodal Models Describe Images From Memory?
di: Aerni, Michael, et al.
Pubblicazione: (2025)

Black-box Optimization of LLM Outputs by Asking for Directions
di: Zhang, Jie, et al.
Pubblicazione: (2025)

Revisiting the LiRA Membership Inference Attack Under Realistic Assumptions
di: Jebreel, Najeeb, et al.
Pubblicazione: (2026)

A Critical Review on the Effectiveness and Privacy Threats of Membership Inference Attacks
di: Jebreel, Najeeb, et al.
Pubblicazione: (2026)

Evading Black-box Classifiers Without Breaking Eggs
di: Debenedetti, Edoardo, et al.
Pubblicazione: (2023)

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
di: Tramèr, Florian, et al.
Pubblicazione: (2022)