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MagNet and "Efficient Defenses Against Adversarial Attacks" are Not
  Robust to Adversarial Examples

MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples

22 November 2017
Nicholas Carlini
D. Wagner
    AAML
ArXiv (abs)PDFHTML

Papers citing "MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples"

35 / 135 papers shown
Random Spiking and Systematic Evaluation of Defenses Against Adversarial
  Examples
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples
Huangyi Ge
Sze Yiu Chau
Bruno Ribeiro
Ninghui Li
AAML
208
1
0
05 Dec 2018
The Taboo Trap: Behavioural Detection of Adversarial Samples
The Taboo Trap: Behavioural Detection of Adversarial Samples
Ilia Shumailov
Yiren Zhao
Robert D. Mullins
Ross J. Anderson
AAML
150
16
0
18 Nov 2018
MixTrain: Scalable Training of Verifiably Robust Neural Networks
MixTrain: Scalable Training of Verifiably Robust Neural Networks
Yue Zhang
Yizheng Chen
Ahmed Abdou
Mohsen Guizani
AAML
92
25
0
06 Nov 2018
Blockchain and human episodic memory
Blockchain and human episodic memory
S. Cho
Cody A Cushing
Kunal Patel
Alok Kothari
Rongjian Lan
Matthew Mattina
Mouslim Cherkaoui
Hakwan Lau
89
1
0
06 Nov 2018
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural
  Network against Adversarial Attacks
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks
Faiq Khalid
Hassan Ali
Hammad Tariq
Muhammad Abdullah Hanif
Semeen Rehman
Rehan Ahmed
Mohamed Bennai
AAMLMQ
202
38
0
04 Nov 2018
On Extensions of CLEVER: A Neural Network Robustness Evaluation
  Algorithm
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm
Tsui-Wei Weng
Huan Zhang
Pin-Yu Chen
A. Lozano
Cho-Jui Hsieh
Luca Daniel
114
13
0
19 Oct 2018
Security Matters: A Survey on Adversarial Machine Learning
Security Matters: A Survey on Adversarial Machine Learning
Guofu Li
Pengjia Zhu
Jin Li
Zhemin Yang
Ning Cao
Zhiyi Chen
AAML
221
27
0
16 Oct 2018
The Adversarial Attack and Detection under the Fisher Information Metric
The Adversarial Attack and Detection under the Fisher Information Metric
Chenxiao Zhao
P. T. Fletcher
Mixue Yu
Chaomin Shen
Guixu Zhang
Yaxin Peng
AAML
197
50
0
09 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon
Adversarial Examples - A Complete Characterisation of the Phenomenon
A. Serban
E. Poll
Joost Visser
SILMAAML
246
49
0
02 Oct 2018
Characterizing Audio Adversarial Examples Using Temporal Dependency
Characterizing Audio Adversarial Examples Using Temporal DependencyInternational Conference on Learning Representations (ICLR), 2018
Zhuolin Yang
Yue Liu
Pin-Yu Chen
Basel Alomair
AAML
199
172
0
28 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural
  Networks against Adversarial Malware Samples
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples
Deqiang Li
Ramesh Baral
Tao Li
Zheng Chen
Qianmu Li
Shouhuai Xu
AAML
158
22
0
18 Sep 2018
Certified Adversarial Robustness with Additive Noise
Certified Adversarial Robustness with Additive Noise
Bai Li
Changyou Chen
Wenlin Wang
Lawrence Carin
AAML
436
369
0
10 Sep 2018
Are adversarial examples inevitable?
Are adversarial examples inevitable?
Ali Shafahi
Wenjie Huang
Christoph Studer
Soheil Feizi
Tom Goldstein
SILM
400
291
0
06 Sep 2018
ATMPA: Attacking Machine Learning-based Malware Visualization Detection
  Methods via Adversarial Examples
ATMPA: Attacking Machine Learning-based Malware Visualization Detection Methods via Adversarial Examples
Xinbo Liu
Jiliang Zhang
Yaping Lin
He Li
AAML
197
60
0
05 Aug 2018
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
Logan Engstrom
Andrew Ilyas
Anish Athalye
AAML
253
145
0
26 Jul 2018
Simultaneous Adversarial Training - Learn from Others Mistakes
Simultaneous Adversarial Training - Learn from Others MistakesIEEE International Conference on Automatic Face & Gesture Recognition (FG), 2018
Zukang Liao
AAMLGAN
173
4
0
21 Jul 2018
Gradient Similarity: An Explainable Approach to Detect Adversarial
  Attacks against Deep Learning
Gradient Similarity: An Explainable Approach to Detect Adversarial Attacks against Deep Learning
J. Dhaliwal
S. Shintre
AAML
84
16
0
27 Jun 2018
PAC-learning in the presence of evasion adversaries
PAC-learning in the presence of evasion adversaries
Daniel Cullina
A. Bhagoji
Prateek Mittal
AAML
199
56
0
05 Jun 2018
Detecting Adversarial Examples via Key-based Network
Detecting Adversarial Examples via Key-based Network
Pinlong Zhao
Zhouyu Fu
Ou Wu
Q. Hu
Jun Wang
AAMLGAN
173
8
0
02 Jun 2018
Resisting Adversarial Attacks using Gaussian Mixture Variational
  Autoencoders
Resisting Adversarial Attacks using Gaussian Mixture Variational Autoencoders
Partha Ghosh
Arpan Losalka
Michael J. Black
AAML
236
81
0
31 May 2018
Towards the first adversarially robust neural network model on MNIST
Towards the first adversarially robust neural network model on MNIST
Lukas Schott
Jonas Rauber
Matthias Bethge
Wieland Brendel
AAMLOOD
344
380
0
23 May 2018
Towards Fast Computation of Certified Robustness for ReLU Networks
Towards Fast Computation of Certified Robustness for ReLU Networks
Tsui-Wei Weng
Huan Zhang
Hongge Chen
Zhao Song
Cho-Jui Hsieh
Duane S. Boning
Inderjit S. Dhillon
Luca Daniel
AAML
337
731
0
25 Apr 2018
On the Limitation of MagNet Defense against $L_1$-based Adversarial
  Examples
On the Limitation of MagNet Defense against L1L_1L1​-based Adversarial Examples
Pei-Hsuan Lu
Pin-Yu Chen
Kang-Cheng Chen
Chia-Mu Yu
AAML
268
20
0
14 Apr 2018
Unifying Bilateral Filtering and Adversarial Training for Robust Neural
  Networks
Unifying Bilateral Filtering and Adversarial Training for Robust Neural Networks
Neale Ratzlaff
Fuxin Li
AAMLFedML
113
1
0
05 Apr 2018
Defending against Adversarial Attack towards Deep Neural Networks via
  Collaborative Multi-task Training
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task TrainingIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2018
Derui Wang
Chaoran Li
S. Wen
Surya Nepal
Yang Xiang
AAML
252
35
0
14 Mar 2018
Detecting Adversarial Examples via Neural Fingerprinting
Detecting Adversarial Examples via Neural Fingerprinting
Sumanth Dathathri
Stephan Zheng
Tianwei Yin
Richard M. Murray
Yisong Yue
MLAUAAML
163
0
0
11 Mar 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs
DARTS: Deceiving Autonomous Cars with Toxic Signs
Chawin Sitawarin
A. Bhagoji
Arsalan Mosenia
M. Chiang
Prateek Mittal
AAML
316
245
0
18 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
2.5K
3,380
0
01 Feb 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text
Nicholas Carlini
D. Wagner
AAML
215
1,143
0
05 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Lin Wang
AAML
494
1,993
0
02 Jan 2018
The Robust Manifold Defense: Adversarial Training using Generative
  Models
The Robust Manifold Defense: Adversarial Training using Generative Models
A. Jalal
Andrew Ilyas
C. Daskalakis
A. Dimakis
AAML
418
175
0
26 Dec 2017
Adversarial Examples: Attacks and Defenses for Deep Learning
Adversarial Examples: Attacks and Defenses for Deep LearningIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2017
Xiaoyong Yuan
Pan He
Qile Zhu
Xiaolin Li
SILMAAML
577
1,742
0
19 Dec 2017
Reinforcing Adversarial Robustness using Model Confidence Induced by
  Adversarial Training
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training
Xi Wu
Uyeong Jang
Jiefeng Chen
Lingjiao Chen
S. Jha
AAML
220
21
0
21 Nov 2017
One pixel attack for fooling deep neural networks
One pixel attack for fooling deep neural networksIEEE Transactions on Evolutionary Computation (IEEE TEVC), 2017
Jiawei Su
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
672
2,496
0
24 Oct 2017
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning
B. Rouhani
Mohammad Samragh
Mojan Javaheripi
T. Javidi
F. Koushanfar
AAML
228
15
0
08 Sep 2017
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