HAMIATCM: high-availability membership inference attack against text classification models under little knowledge

Author:

Cheng YaoORCID,Luo SenlinORCID,Pan LiminORCID,Wan YunweiORCID,Li XinshuaiORCID

Funder

National Computer Network Emergency Response Technical Team/Coordination Center of China

Publisher

Springer Science and Business Media LLC

Reference38 articles.

1. Hu H, Salcic Z, Sun L et al (2022) Membership inference attacks on machine learning: a survey. ACM Comput Surv (CSUR) 54(11s):1–37

2. Vakili T (2023) Attacking and defending the privacy of clinical language models[D]. Department of Computer and Systems Sciences, Stockholm University

3. Vakili T, Dalianis H (2021) Are clinical BERT models privacy preserving? The difficulty of extracting patient-condition associations[C]. Proceedings of the AAAI 2021 Fall Symposium on Human Partnership with Medical AI: Design, Operationalization, and Ethics

4. Zhang M, Ren Z, Wang Z et al (2021) Membership inference attacks against recommender systems[C]. Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security, 864–879

5. Zhang G, Liu B, Zhu T et al (2022) Label-only membership inference attacks and defenses in semantic segmentation models. IEEE Trans Dependable Secur Comput 20(2):1435–1449

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