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Adversarial examples in the physical world
v1v2v3v4 (latest)

Adversarial examples in the physical world

8 July 2016
Alexey Kurakin
Ian Goodfellow
Samy Bengio
    SILMAAML
ArXiv (abs)PDFHTML

Papers citing "Adversarial examples in the physical world"

50 / 2,769 papers shown
Title
HoneyModels: Machine Learning Honeypots
HoneyModels: Machine Learning Honeypots
Ahmed Abdou
Ryan Sheatsley
Yohan Beugin
Tyler J. Shipp
Patrick McDaniel
AAML
53
3
0
21 Feb 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient
  Training
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen
Zhenyu Zhang
Pengju Wang
Santosh Balachandra
Haoyu Ma
Zehao Wang
Zhangyang Wang
OODAAML
149
50
0
20 Feb 2022
Real-time Over-the-air Adversarial Perturbations for Digital
  Communications using Deep Neural Networks
Real-time Over-the-air Adversarial Perturbations for Digital Communications using Deep Neural Networks
R. Sandler
Peter K. Relich
Cloud Cho
Sean Holloway
AAML
41
5
0
20 Feb 2022
Learning Representations Robust to Group Shifts and Adversarial Examples
Learning Representations Robust to Group Shifts and Adversarial Examples
Ming-Chang Chiu
Xuezhe Ma
OOD
49
0
0
18 Feb 2022
StratDef: Strategic Defense Against Adversarial Attacks in ML-based
  Malware Detection
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection
Aqib Rashid
Jose Such
AAML
72
7
0
15 Feb 2022
Unreasonable Effectiveness of Last Hidden Layer Activations for
  Adversarial Robustness
Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial Robustness
Ömer Faruk Tuna
Ferhat Ozgur Catak
M. T. Eskil
AAML
35
4
0
15 Feb 2022
Robust Deepfake On Unrestricted Media: Generation And Detection
Robust Deepfake On Unrestricted Media: Generation And Detection
Trung-Nghia Le
H. Nguyen
Junichi Yamagishi
Isao Echizen
97
7
0
13 Feb 2022
Adversarial Attacks and Defense Methods for Power Quality Recognition
Adversarial Attacks and Defense Methods for Power Quality Recognition
Jiwei Tian
Buhong Wang
Jing Li
Zhen Wang
Mete Ozay
AAML
102
0
0
11 Feb 2022
On the Detection of Adaptive Adversarial Attacks in Speaker Verification
  Systems
On the Detection of Adaptive Adversarial Attacks in Speaker Verification Systems
Zesheng Chen
AAML
62
8
0
11 Feb 2022
Adversarial Detection without Model Information
Adversarial Detection without Model Information
Abhishek Moitra
Youngeun Kim
Priyadarshini Panda
AAML
49
1
0
09 Feb 2022
Towards Compositional Adversarial Robustness: Generalizing Adversarial
  Training to Composite Semantic Perturbations
Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations
Lei Hsiung
Yun-Yun Tsai
Pin-Yu Chen
Tsung-Yi Ho
AAML
79
30
0
09 Feb 2022
Verification-Aided Deep Ensemble Selection
Verification-Aided Deep Ensemble Selection
Guy Amir
Tom Zelazny
Guy Katz
Michael Schapira
AAML
114
18
0
08 Feb 2022
Attacking c-MARL More Effectively: A Data Driven Approach
Attacking c-MARL More Effectively: A Data Driven Approach
Nhan H. Pham
Lam M. Nguyen
Jie Chen
Hoang Thanh Lam
Subhro Das
Tsui-Wei Weng
AAML
99
2
0
07 Feb 2022
Robust Semantic Communications Against Semantic Noise
Robust Semantic Communications Against Semantic Noise
Qiyu Hu
Guangyi Zhang
Zhijin Qin
Yunlong Cai
Guanding Yu
Geoffrey Ye Li
AAML
65
83
0
07 Feb 2022
Transformers in Self-Supervised Monocular Depth Estimation with Unknown
  Camera Intrinsics
Transformers in Self-Supervised Monocular Depth Estimation with Unknown Camera Intrinsics
Arnav Varma
Hemang Chawla
Bahram Zonooz
Elahe Arani
ViTMDE
75
50
0
07 Feb 2022
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Lossy Compression of Noisy Data for Private and Data-Efficient Learning
Berivan Isik
Tsachy Weissman
75
3
0
07 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability
  Analysis (LSA) framework
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework
Mohammad Khalooei
M. Homayounpour
M. Amirmazlaghani
AAML
71
3
0
05 Feb 2022
Memory Defense: More Robust Classification via a Memory-Masking
  Autoencoder
Memory Defense: More Robust Classification via a Memory-Masking Autoencoder
Eashan Adhikarla
Danni Luo
Brian D. Davison
AAML
36
2
0
05 Feb 2022
Robust Binary Models by Pruning Randomly-initialized Networks
Robust Binary Models by Pruning Randomly-initialized Networks
Chen Liu
Ziqi Zhao
Sabine Süsstrunk
Mathieu Salzmann
TPMAAMLMQ
87
4
0
03 Feb 2022
An Eye for an Eye: Defending against Gradient-based Attacks with
  Gradients
An Eye for an Eye: Defending against Gradient-based Attacks with Gradients
Hanbin Hong
Yuan Hong
Yu Kong
AAML
65
2
0
02 Feb 2022
MEGA: Model Stealing via Collaborative Generator-Substitute Networks
MEGA: Model Stealing via Collaborative Generator-Substitute Networks
Chi Hong
Jiyue Huang
L. Chen
65
2
0
31 Jan 2022
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained
  Encoders
SSLGuard: A Watermarking Scheme for Self-supervised Learning Pre-trained Encoders
Tianshuo Cong
Xinlei He
Yang Zhang
92
55
0
27 Jan 2022
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for
  Black-box Domains
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains
Qilong Zhang
Xiaodan Li
YueFeng Chen
Jingkuan Song
Lianli Gao
Yuan He
Hui Xue
AAML
171
67
0
27 Jan 2022
How Robust are Discriminatively Trained Zero-Shot Learning Models?
How Robust are Discriminatively Trained Zero-Shot Learning Models?
M. K. Yucel
R. G. Cinbis
Pinar Duygulu
86
14
0
26 Jan 2022
What You See is Not What the Network Infers: Detecting Adversarial
  Examples Based on Semantic Contradiction
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
GANAAML
106
20
0
24 Jan 2022
Efficient and Robust Classification for Sparse Attacks
Efficient and Robust Classification for Sparse Attacks
M. Beliaev
Payam Delgosha
Hamed Hassani
Ramtin Pedarsani
AAML
56
2
0
23 Jan 2022
Deeply Explain CNN via Hierarchical Decomposition
Deeply Explain CNN via Hierarchical Decomposition
Mingg-Ming Cheng
Peng-Tao Jiang
Linghao Han
Liang Wang
Philip Torr
FAtt
96
15
0
23 Jan 2022
Enhancing the Security & Privacy of Wearable Brain-Computer Interfaces
Enhancing the Security & Privacy of Wearable Brain-Computer Interfaces
Zahra Tarkhani
Lorena Qendro
Malachy O'Connor Brown
Oscar Hill
Cecilia Mascolo
Anil Madhavapeddy
56
9
0
19 Jan 2022
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image
  Encoders
Can't Steal? Cont-Steal! Contrastive Stealing Attacks Against Image Encoders
Zeyang Sha
Xinlei He
Ning Yu
Michael Backes
Yang Zhang
140
35
0
19 Jan 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial
  Examples Against Traffic Sign Recognition Systems
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems
Wei Jia
Zhaojun Lu
Haichun Zhang
Zhenglin Liu
Jie Wang
Gang Qu
AAML
71
54
0
17 Jan 2022
Adversarial Machine Learning Threat Analysis and Remediation in Open
  Radio Access Network (O-RAN)
Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)
Edan Habler
Ron Bitton
D. Avraham
D. Mimran
Eitan Klevansky
Oleg Brodt
Heiko Lehmann
Yuval Elovici
A. Shabtai
AAML
87
14
0
16 Jan 2022
ALA: Naturalness-aware Adversarial Lightness Attack
ALA: Naturalness-aware Adversarial Lightness Attack
Yihao Huang
Liangru Sun
Qing Guo
Felix Juefei Xu
Jiayi Zhu
Jincao Feng
Yang Liu
G. Pu
AAML
92
11
0
16 Jan 2022
Adversarially Robust Classification by Conditional Generative Model
  Inversion
Adversarially Robust Classification by Conditional Generative Model Inversion
Mitra Alirezaei
Tolga Tasdizen
AAML
40
0
0
12 Jan 2022
Get your Foes Fooled: Proximal Gradient Split Learning for Defense
  against Model Inversion Attacks on IoMT data
Get your Foes Fooled: Proximal Gradient Split Learning for Defense against Model Inversion Attacks on IoMT data
Sunder Ali Khowaja
I. Lee
Kapal Dev
M. Jarwar
N. Qureshi
AAML
88
16
0
12 Jan 2022
Towards Adversarially Robust Deep Image Denoising
Towards Adversarially Robust Deep Image Denoising
Hanshu Yan
Jingfeng Zhang
Jiashi Feng
Masashi Sugiyama
Vincent Y. F. Tan
DiffM
57
17
0
12 Jan 2022
Evaluation of Neural Networks Defenses and Attacks using NDCG and
  Reciprocal Rank Metrics
Evaluation of Neural Networks Defenses and Attacks using NDCG and Reciprocal Rank Metrics
Haya Brama
L. Dery
Tal Grinshpoun
AAML
66
8
0
10 Jan 2022
Rethink the Evaluation for Attack Strength of Backdoor Attacks in
  Natural Language Processing
Rethink the Evaluation for Attack Strength of Backdoor Attacks in Natural Language Processing
Lingfeng Shen
Haiyun Jiang
Lemao Liu
Shuming Shi
ELM
31
1
0
09 Jan 2022
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution
  Detection
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection
R. Kaur
Susmit Jha
Anirban Roy
Sangdon Park
Yan Sun
O. Sokolsky
Insup Lee
OODD
66
47
0
07 Jan 2022
On the Real-World Adversarial Robustness of Real-Time Semantic
  Segmentation Models for Autonomous Driving
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving
Giulio Rossolini
F. Nesti
G. D’Amico
Saasha Nair
Alessandro Biondi
Giorgio Buttazzo
AAML
86
42
0
05 Jan 2022
ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints
ROOM: Adversarial Machine Learning Attacks Under Real-Time Constraints
Amira Guesmi
Khaled N. Khasawneh
Nael B. Abu-Ghazaleh
Ihsen Alouani
AAML
52
14
0
05 Jan 2022
Towards Transferable Unrestricted Adversarial Examples with Minimum
  Changes
Towards Transferable Unrestricted Adversarial Examples with Minimum Changes
Fangcheng Liu
Chaoning Zhang
Hongyang R. Zhang
AAML
88
21
0
04 Jan 2022
Towards Understanding and Harnessing the Effect of Image Transformation
  in Adversarial Detection
Towards Understanding and Harnessing the Effect of Image Transformation in Adversarial Detection
Hui Liu
Bo Zhao
Yuefeng Peng
Weidong Li
Peng Liu
AAML
90
1
0
04 Jan 2022
Revisiting PGD Attacks for Stability Analysis of Large-Scale Nonlinear
  Systems and Perception-Based Control
Revisiting PGD Attacks for Stability Analysis of Large-Scale Nonlinear Systems and Perception-Based Control
Aaron J. Havens
Darioush Keivan
Peter M. Seiler
Geir Dullerud
Bin Hu
AAML
57
3
0
03 Jan 2022
Adversarial Attack via Dual-Stage Network Erosion
Adversarial Attack via Dual-Stage Network Erosion
Yexin Duan
Junhua Zou
Xingyu Zhou
Wu Zhang
Jin Zhang
Zhisong Pan
AAMLSILM
64
5
0
01 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification
Benign Overfitting in Adversarially Robust Linear Classification
Jinghui Chen
Yuan Cao
Quanquan Gu
AAMLSILM
78
11
0
31 Dec 2021
Semantic Communications: Principles and Challenges
Semantic Communications: Principles and Challenges
Zhijin Qin
Xiaoming Tao
Jianhua Lu
Wen Tong
Geoffrey Ye Li
143
350
0
30 Dec 2021
Improving the Behaviour of Vision Transformers with Token-consistent
  Stochastic Layers
Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers
Nikola Popovic
D. Paudel
Thomas Probst
Luc Van Gool
82
1
0
30 Dec 2021
Invertible Image Dataset Protection
Invertible Image Dataset Protection
Kejiang Chen
Xianhan Zeng
Qichao Ying
Sheng Li
Zhenxing Qian
Xinpeng Zhang
71
7
0
29 Dec 2021
Closer Look at the Transferability of Adversarial Examples: How They
  Fool Different Models Differently
Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently
Futa Waseda
Sosuke Nishikawa
Trung-Nghia Le
H. Nguyen
Isao Echizen
SILM
96
37
0
29 Dec 2021
Constrained Gradient Descent: A Powerful and Principled Evasion Attack
  Against Neural Networks
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
Weiran Lin
Keane Lucas
Lujo Bauer
Michael K. Reiter
Mahmood Sharif
AAML
63
5
0
28 Dec 2021
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