BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models

Details

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Serval ID
serval:BIB_72B9CC50208C
Type
Report: a report published by a school or other institution, usually numbered within a series.
Publication sub-type
Working paper: Working papers contain results presented by the author. Working papers aim to stimulate discussions between scientists with interested parties, they can also be the basis to publish articles in specialized journals
Collection
Publications
Institution
UNIL/CHUV
Title
BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models
Author(s)
Salem Ahmed, Sautter Yannick, Backes Michael, Humbert Mathias, Zhang Yang
Institution details
Université de Lausanne, HEC Lausanne
Issued date
08/10/2020
Volume
abs/2010.03007
Language
english
URN
urn:nbn:ch:serval-BIB_72B9CC50208C3
OAI-PMH
oai:serval.unil.ch:BIB_72B9CC50208C
Publisher's website
https://arxiv.org/abs/2010.03007
Create date
05/11/2021 10:59
Last modification date
21/11/2022 8:20
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