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MagNet: a Two-Pronged Defense against Adversarial Examples
v1v2 (latest)

MagNet: a Two-Pronged Defense against Adversarial Examples

25 May 2017
Dongyu Meng
Hao Chen
    AAML
ArXiv (abs)PDFHTML

Papers citing "MagNet: a Two-Pronged Defense against Adversarial Examples"

31 / 31 papers shown
Title
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
Wenyuan Wu
Zheng Liu
Yong Chen
Chao Su
Dezhong Peng
Xu Wang
AAML
184
0
0
24 Feb 2025
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems
Guangjing Wang
Ce Zhou
Yuanda Wang
Bocheng Chen
Hanqing Guo
Qiben Yan
AAMLSILM
125
3
0
20 Nov 2023
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for
  Adversary Defense
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense
Jingyuan Wang
Yufan Wu
Mingxuan Li
Xin Lin
Junjie Wu
Chao Li
AAML
50
13
0
14 Apr 2023
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
Yonggan Fu
Yang Zhao
Qixuan Yu
Chaojian Li
Yingyan Lin
AAML
114
14
0
11 Sep 2021
Adversarial Examples on Object Recognition: A Comprehensive Survey
Adversarial Examples on Object Recognition: A Comprehensive Survey
A. Serban
E. Poll
Joost Visser
AAML
105
73
0
07 Aug 2020
Deep Learning for Medical Image Analysis
Deep Learning for Medical Image Analysis
Mina Rezaei
Haojin Yang
Christoph Meinel
77
2,072
0
17 Aug 2017
Robustness of classifiers to universal perturbations: a geometric
  perspective
Robustness of classifiers to universal perturbations: a geometric perspective
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
Stefano Soatto
AAML
75
118
0
26 May 2017
Adversarial Examples for Semantic Segmentation and Object Detection
Adversarial Examples for Semantic Segmentation and Object Detection
Cihang Xie
Jianyu Wang
Zhishuai Zhang
Yuyin Zhou
Lingxi Xie
Alan Yuille
GANAAML
111
934
0
24 Mar 2017
Adversarial examples for generative models
Adversarial examples for generative models
Jernej Kos
Ian S. Fischer
Basel Alomair
GAN
86
274
0
22 Feb 2017
On the (Statistical) Detection of Adversarial Examples
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse
Praveen Manoharan
Nicolas Papernot
Michael Backes
Patrick McDaniel
AAML
86
714
0
21 Feb 2017
On Detecting Adversarial Perturbations
On Detecting Adversarial Perturbations
J. H. Metzen
Tim Genewein
Volker Fischer
Bastian Bischoff
AAML
73
950
0
14 Feb 2017
Uncertainty-Aware Reinforcement Learning for Collision Avoidance
Uncertainty-Aware Reinforcement Learning for Collision Avoidance
G. Kahn
Adam R. Villaflor
Vitchyr H. Pong
Pieter Abbeel
Sergey Levine
102
316
0
03 Feb 2017
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
Basel Alomair
AAML
143
1,741
0
08 Nov 2016
Universal adversarial perturbations
Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
Omar Fawzi
P. Frossard
AAML
152
2,533
0
26 Oct 2016
Deep Visual Foresight for Planning Robot Motion
Deep Visual Foresight for Planning Robot Motion
Chelsea Finn
Sergey Levine
123
788
0
03 Oct 2016
Towards Evaluating the Robustness of Neural Networks
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OODAAML
282
8,587
0
16 Aug 2016
Learning Transferable Policies for Monocular Reactive MAV Control
Learning Transferable Policies for Monocular Reactive MAV Control
S. Daftry
J. Andrew Bagnell
Martial Hebert
68
85
0
01 Aug 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
547
5,912
0
08 Jul 2016
Adversarial Perturbations Against Deep Neural Networks for Malware
  Classification
Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Kathrin Grosse
Nicolas Papernot
Praveen Manoharan
Michael Backes
Patrick McDaniel
AAML
79
418
0
14 Jun 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Nicolas Papernot
Patrick McDaniel
A. Swami
Richard E. Harang
AAMLGANSILM
61
456
0
28 Apr 2016
End to End Learning for Self-Driving Cars
End to End Learning for Self-Driving Cars
Mariusz Bojarski
D. Testa
Daniel Dworakowski
Bernhard Firner
B. Flepp
...
Urs Muller
Jiakai Zhang
Xin Zhang
Jake Zhao
Karol Zieba
SSL
102
4,178
0
25 Apr 2016
Practical Black-Box Attacks against Machine Learning
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot
Patrick McDaniel
Ian Goodfellow
S. Jha
Z. Berkay Celik
A. Swami
MLAUAAML
75
3,685
0
08 Feb 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,510
0
10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
117
3,968
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
154
4,905
0
14 Nov 2015
Distillation as a Defense to Adversarial Perturbations against Deep
  Neural Networks
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
Nicolas Papernot
Patrick McDaniel
Xi Wu
S. Jha
A. Swami
AAML
118
3,077
0
14 Nov 2015
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
A. Kumar
Ozan Irsoy
Peter Ondruska
Mohit Iyyer
James Bradbury
Ishaan Gulrajani
Victor Zhong
Romain Paulus
R. Socher
118
1,182
0
24 Jun 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
367
19,745
0
09 Mar 2015
Striving for Simplicity: The All Convolutional Net
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
254
4,681
0
21 Dec 2014
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,129
0
20 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
289
14,968
1
21 Dec 2013
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