ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Details

Ressource 1Download: ndss19_1.pdf (595.83 [Ko])
State: Public
Version: Final published version
License: Not specified
Serval ID
serval:BIB_84C51526C92A
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
UNIL/CHUV
Title
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
Title of the conference
26th Annual Network and Distributed System Security Symposium, NDSS 2019, San Diego, California, USA, February 24-27, 2019
Author(s)
Salem Ahmed, Zhang Yang, Humbert Mathias, Berrang Pascal, Fritz Mario, Backes Michael
Publisher
The Internet Society
Publication state
Published
Issued date
2019
Peer-reviewed
Oui
Language
english
URN
urn:nbn:ch:serval-BIB_84C51526C92A3
OAI-PMH
oai:serval.unil.ch:BIB_84C51526C92A
Publisher's website
https://www.ndss-symposium.org/ndss-paper/ml-leaks-model-and-data-independent-membership-inference-attacks-and-defenses-on-machine-learning-models/
Create date
05/11/2021 10:59
Last modification date
15/11/2021 7:11
Usage data