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Towards Evaluating the Robustness of Neural Networks
v1v2 (latest)

Towards Evaluating the Robustness of Neural Networks

16 August 2016
Nicholas Carlini
D. Wagner
    OODAAML
ArXiv (abs)PDFHTML

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 4,100 papers shown
Title
Adversarial Neon Beam: A Light-based Physical Attack to DNNs
Adversarial Neon Beam: A Light-based Physical Attack to DNNs
Chen-Hao Hu
Weiwen Shi
Wen Li
AAML
108
9
0
02 Apr 2022
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting
FrequencyLowCut Pooling -- Plug & Play against Catastrophic Overfitting
Julia Grabinski
Steffen Jung
J. Keuper
Margret Keuper
AAML
79
22
0
01 Apr 2022
Simulator-based explanation and debugging of hazard-triggering events in
  DNN-based safety-critical systems
Simulator-based explanation and debugging of hazard-triggering events in DNN-based safety-critical systems
Hazem M. Fahmy
F. Pastore
Lionel C. Briand
Thomas Stifter
AAML
103
15
0
01 Apr 2022
Improving Adversarial Transferability via Neuron Attribution-Based
  Attacks
Improving Adversarial Transferability via Neuron Attribution-Based Attacks
Jianping Zhang
Weibin Wu
Jen-tse Huang
Yizhan Huang
Wenxuan Wang
Yuxin Su
Michael R. Lyu
AAML
106
136
0
31 Mar 2022
Investigating Top-$k$ White-Box and Transferable Black-box Attack
Investigating Top-kkk White-Box and Transferable Black-box Attack
Chaoning Zhang
Philipp Benz
Adil Karjauv
Jae-Won Cho
Kang Zhang
In So Kweon
94
44
0
30 Mar 2022
StyleFool: Fooling Video Classification Systems via Style Transfer
StyleFool: Fooling Video Classification Systems via Style Transfer
Yu Cao
Xi Xiao
Ruoxi Sun
Derui Wang
Minhui Xue
Sheng Wen
AAML
131
26
0
30 Mar 2022
Recent improvements of ASR models in the face of adversarial attacks
Recent improvements of ASR models in the face of adversarial attacks
R. Olivier
Bhiksha Raj
AAML
126
14
0
29 Mar 2022
NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image
  Caption Generation Models
NICGSlowDown: Evaluating the Efficiency Robustness of Neural Image Caption Generation Models
Simin Chen
Zihe Song
Mirazul Haque
Cong Liu
Wei Yang
80
42
0
29 Mar 2022
Zero-Query Transfer Attacks on Context-Aware Object Detectors
Zero-Query Transfer Attacks on Context-Aware Object Detectors
Zikui Cai
S. Rane
Alejandro E. Brito
Chengyu Song
S. Krishnamurthy
Amit K. Roy-Chowdhury
M. Salman Asif
AAML
71
23
0
29 Mar 2022
Boosting Black-Box Adversarial Attacks with Meta Learning
Boosting Black-Box Adversarial Attacks with Meta Learning
Junjie Fu
Jian Sun
Chongqing
AAML
36
4
0
28 Mar 2022
Robust Unlearnable Examples: Protecting Data Against Adversarial
  Learning
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning
Shaopeng Fu
Fengxiang He
Yang Liu
Li Shen
Dacheng Tao
80
26
0
28 Mar 2022
Text Adversarial Purification as Defense against Adversarial Attacks
Text Adversarial Purification as Defense against Adversarial Attacks
Linyang Li
Demin Song
Xipeng Qiu
AAML
79
17
0
27 Mar 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization
  Perspective
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
129
34
0
27 Mar 2022
Reverse Engineering of Imperceptible Adversarial Image Perturbations
Reverse Engineering of Imperceptible Adversarial Image Perturbations
Yifan Gong
Yuguang Yao
Yize Li
Yimeng Zhang
Xiaoming Liu
Xinyu Lin
Sijia Liu
AAML
172
21
0
26 Mar 2022
A Survey of Robust Adversarial Training in Pattern Recognition:
  Fundamental, Theory, and Methodologies
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OODAAMLObjD
128
73
0
26 Mar 2022
A Manifold View of Adversarial Risk
A Manifold View of Adversarial Risk
Wen-jun Zhang
Yikai Zhang
Xiaoling Hu
Mayank Goswami
Chao Chen
Dimitris N. Metaxas
AAML
65
6
0
24 Mar 2022
A Perturbation-Constrained Adversarial Attack for Evaluating the
  Robustness of Optical Flow
A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow
Jenny Schmalfuss
Philipp Scholze
Andrés Bruhn
AAML
86
19
0
24 Mar 2022
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep
  Neural Networks
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks
Xiaofei Xie
Tianlin Li
Jian-Xun Wang
Lei Ma
Qing Guo
Felix Juefei Xu
Yang Liu
AAML
95
55
0
24 Mar 2022
Powerful Physical Adversarial Examples Against Practical Face
  Recognition Systems
Powerful Physical Adversarial Examples Against Practical Face Recognition Systems
Inderjeet Singh
Toshinori Araki
Kazuya Kakizaki
AAML
101
13
0
23 Mar 2022
Making DeepFakes more spurious: evading deep face forgery detection via
  trace removal attack
Making DeepFakes more spurious: evading deep face forgery detection via trace removal attack
Chi Liu
Huajie Chen
Tianqing Zhu
Jun Zhang
Wanlei Zhou
AAML
71
24
0
22 Mar 2022
PublicCheck: Public Integrity Verification for Services of Run-time Deep
  Models
PublicCheck: Public Integrity Verification for Services of Run-time Deep Models
Shuo Wang
Sharif Abuadbba
Sidharth Agarwal
Kristen Moore
Ruoxi Sun
Minhui Xue
Surya Nepal
S. Çamtepe
S. Kanhere
HILM
78
7
0
21 Mar 2022
Adversarial Parameter Attack on Deep Neural Networks
Adversarial Parameter Attack on Deep Neural Networks
Lijia Yu
Yihan Wang
Xiao-Shan Gao
AAML
76
9
0
20 Mar 2022
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Efficient Neural Network Analysis with Sum-of-Infeasibilities
Haoze Wu
Aleksandar Zeljić
Guy Katz
Clark W. Barrett
AAML
113
31
0
19 Mar 2022
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on
  Deep Learning-based Video Compression
RoVISQ: Reduction of Video Service Quality via Adversarial Attacks on Deep Learning-based Video Compression
Jung-Woo Chang
Mojan Javaheripi
Seira Hidano
F. Koushanfar
98
8
0
18 Mar 2022
Towards Robust 2D Convolution for Reliable Visual Recognition
Towards Robust 2D Convolution for Reliable Visual Recognition
Lida Li
Shuai Li
Kun Wang
Xiangchu Feng
Lei Zhang
43
1
0
18 Mar 2022
AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack
AutoAdversary: A Pixel Pruning Method for Sparse Adversarial Attack
Jinqiao Li
Xiaotao Liu
Jian Zhao
S. Furao
AAML
34
1
0
18 Mar 2022
Self-Ensemble Adversarial Training for Improved Robustness
Self-Ensemble Adversarial Training for Improved Robustness
Hongjun Wang
Yisen Wang
OODAAML
65
51
0
18 Mar 2022
Provable Adversarial Robustness for Fractional Lp Threat Models
Provable Adversarial Robustness for Fractional Lp Threat Models
Alexander Levine
Soheil Feizi
25
2
0
16 Mar 2022
What Do Adversarially trained Neural Networks Focus: A Fourier
  Domain-based Study
What Do Adversarially trained Neural Networks Focus: A Fourier Domain-based Study
Binxiao Huang
Chaofan Tao
R. Lin
Ngai Wong
AAMLOOD
60
3
0
16 Mar 2022
Attacking deep networks with surrogate-based adversarial black-box
  methods is easy
Attacking deep networks with surrogate-based adversarial black-box methods is easy
Nicholas A. Lord
Romain Mueller
Luca Bertinetto
AAMLMLAU
141
25
0
16 Mar 2022
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
Y. Fu
Shunyao Zhang
Shan-Hung Wu
Cheng Wan
Yingyan Lin
AAML
124
67
0
16 Mar 2022
Adversarial amplitude swap towards robust image classifiers
Adversarial amplitude swap towards robust image classifiers
Tan Yang
K. Kawamoto
Hiroshi Kera
AAML
40
1
0
14 Mar 2022
Defending Against Adversarial Attack in ECG Classification with
  Adversarial Distillation Training
Defending Against Adversarial Attack in ECG Classification with Adversarial Distillation Training
Jiahao Shao
Shijia Geng
Zhaoji Fu
Wei-Zhao Xu
Tong Liu
linda Qiao
AAML
59
4
0
14 Mar 2022
Generating Practical Adversarial Network Traffic Flows Using NIDSGAN
Generating Practical Adversarial Network Traffic Flows Using NIDSGAN
B. Zolbayar
Ryan Sheatsley
Patrick McDaniel
Mike Weisman
Sencun Zhu
Shitong Zhu
S. Krishnamurthy
GANAAML
56
15
0
13 Mar 2022
LAS-AT: Adversarial Training with Learnable Attack Strategy
LAS-AT: Adversarial Training with Learnable Attack Strategy
Xiaojun Jia
Yong Zhang
Baoyuan Wu
Ke Ma
Jue Wang
Xiaochun Cao
AAML
80
140
0
13 Mar 2022
Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based
  Prior
Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior
Yinpeng Dong
Shuyu Cheng
Tianyu Pang
Hang Su
Jun Zhu
AAML
69
60
0
13 Mar 2022
The worst of both worlds: A comparative analysis of errors in learning
  from data in psychology and machine learning
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning
Jessica Hullman
Sayash Kapoor
Priyanka Nanayakkara
Andrew Gelman
Arvind Narayanan
149
39
0
12 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights
Enhancing Adversarial Training with Second-Order Statistics of Weights
Gao Jin
Xinping Yi
Wei Huang
S. Schewe
Xiaowei Huang
AAML
89
48
0
11 Mar 2022
SoK: On the Semantic AI Security in Autonomous Driving
SoK: On the Semantic AI Security in Autonomous Driving
Junjie Shen
Ningfei Wang
Ziwen Wan
Yunpeng Luo
Takami Sato
...
Zhenyu Zhong
Kang Li
Ziming Zhao
Chunming Qiao
Qi Alfred Chen
AAML
84
41
0
10 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack
Ye Liu
Yaya Cheng
Lianli Gao
Xianglong Liu
Qilong Zhang
Jingkuan Song
AAML
122
61
0
10 Mar 2022
Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity
Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity
Cheng Luo
Qinliang Lin
Weicheng Xie
Bizhu Wu
Jinheng Xie
Linlin Shen
AAML
148
105
0
10 Mar 2022
Reverse Engineering $\ell_p$ attacks: A block-sparse optimization
  approach with recovery guarantees
Reverse Engineering ℓp\ell_pℓp​ attacks: A block-sparse optimization approach with recovery guarantees
D. Thaker
Paris V. Giampouras
René Vidal
AAML
46
6
0
09 Mar 2022
Binary Classification Under $\ell_0$ Attacks for General Noise
  Distribution
Binary Classification Under ℓ0\ell_0ℓ0​ Attacks for General Noise Distribution
Payam Delgosha
Hamed Hassani
Ramtin Pedarsani
AAML
109
0
0
09 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers
Defending Black-box Skeleton-based Human Activity Classifiers
He Wang
Yunfeng Diao
Zichang Tan
G. Guo
AAML
133
10
0
09 Mar 2022
Machine Learning in NextG Networks via Generative Adversarial Networks
Machine Learning in NextG Networks via Generative Adversarial Networks
E. Ayanoglu
Kemal Davaslioglu
Y. Sagduyu
GAN
69
34
0
09 Mar 2022
Adaptative Perturbation Patterns: Realistic Adversarial Learning for
  Robust Intrusion Detection
Adaptative Perturbation Patterns: Realistic Adversarial Learning for Robust Intrusion Detection
João Vitorino
Nuno Oliveira
Isabel Praça
AAML
58
29
0
08 Mar 2022
Robustly-reliable learners under poisoning attacks
Robustly-reliable learners under poisoning attacks
Maria-Florina Balcan
Avrim Blum
Steve Hanneke
Dravyansh Sharma
AAMLOOD
88
16
0
08 Mar 2022
Shape-invariant 3D Adversarial Point Clouds
Shape-invariant 3D Adversarial Point Clouds
Qidong Huang
Xiaoyi Dong
Dongdong Chen
Hang Zhou
Weiming Zhang
Nenghai Yu
3DPC
101
73
0
08 Mar 2022
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via
  Adversarial Rotation
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation
Robin Wang
Yibo Yang
Dacheng Tao
3DPC
126
18
0
08 Mar 2022
Shadows can be Dangerous: Stealthy and Effective Physical-world
  Adversarial Attack by Natural Phenomenon
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
Yiqi Zhong
Xianming Liu
Deming Zhai
Junjun Jiang
Xiangyang Ji
AAML
165
153
0
08 Mar 2022
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