A survey on membership inference attacks and defenses in machine learning

A survey on membership inference attacks and defenses in machine learning

Membership inference (MI) attacks mainly aim to infer whether a data record was used to train a target model or not. Due to the serious privacy risks, MI attacks have been attracting a tremendous amount of attention in the research community. One existing work conducted — to our best knowledge — the...

Full description

Saved in:
Bibliographic Details
Main Authors: Jun Niu, Peng Liu, Xiaoyan Zhu, Kuo Shen, Yuecong Wang, Haotian Chi, Yulong Shen, Xiaohong Jiang, Jianfeng Ma, Yuqing Zhang
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-09-01
Series:Journal of Information and Intelligence
Subjects:
Machine learning
Privacy and security
Membership inference attacks
Defensive techniques
Online Access:http://www.sciencedirect.com/science/article/pii/S2949715924000064
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2949715924000064

Similar Items