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EMShepherd: Detecting Adversarial Samples via Side-channel Leakage
27 March 2023
Ruyi Ding
Gongye Cheng
Siyue Wang
A. A. Ding
Yunsi Fei
AAML
Re-assign community
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Papers citing
"EMShepherd: Detecting Adversarial Samples via Side-channel Leakage"
4 / 4 papers shown
Title
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
Yijun Yang
Ruiyuan Gao
Yu Li
Qiuxia Lai
Qiang Xu
GAN
AAML
27
20
0
24 Jan 2022
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
948
20,471
0
17 Apr 2017
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,830
0
08 Jul 2016
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
149
9,316
0
28 May 2015
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