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Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box
  Machine Learning Models

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models

12 December 2017
Wieland Brendel
Jonas Rauber
Matthias Bethge
    AAML
ArXivPDFHTML

Papers citing "Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models"

50 / 280 papers shown
Title
Robust One-Class Classification with Signed Distance Function using
  1-Lipschitz Neural Networks
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks
Louis Bethune
Paul Novello
Thibaut Boissin
Guillaume Coiffier
M. Serrurier
Quentin Vincenot
Andres Troya-Galvis
39
8
0
26 Jan 2023
BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense
BEAGLE: Forensics of Deep Learning Backdoor Attack for Better Defense
Shuyang Cheng
Guanhong Tao
Yingqi Liu
Shengwei An
Xiangzhe Xu
...
Guangyu Shen
Kaiyuan Zhang
Qiuling Xu
Shiqing Ma
Xiangyu Zhang
AAML
34
15
0
16 Jan 2023
Generalizable Black-Box Adversarial Attack with Meta Learning
Generalizable Black-Box Adversarial Attack with Meta Learning
Fei Yin
Yong Zhang
Baoyuan Wu
Yan Feng
Jingyi Zhang
Yanbo Fan
Yujiu Yang
AAML
39
27
0
01 Jan 2023
Tracing the Origin of Adversarial Attack for Forensic Investigation and
  Deterrence
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence
Han Fang
Jiyi Zhang
Yupeng Qiu
Ke Xu
Chengfang Fang
E. Chang
AAML
33
2
0
31 Dec 2022
Adversarial attacks and defenses on ML- and hardware-based IoT device
  fingerprinting and identification
Adversarial attacks and defenses on ML- and hardware-based IoT device fingerprinting and identification
Pedro Miguel Sánchez Sánchez
Alberto Huertas Celdrán
Gérome Bovet
Gregorio Martínez Pérez
AAML
29
17
0
30 Dec 2022
Understanding the Vulnerability of Skeleton-based Human Activity
  Recognition via Black-box Attack
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
Yunfeng Diao
He Wang
Tianjia Shao
Yong-Liang Yang
Kun Zhou
David C. Hogg
Meng Wang
AAML
45
7
0
21 Nov 2022
Towards Good Practices in Evaluating Transfer Adversarial Attacks
Towards Good Practices in Evaluating Transfer Adversarial Attacks
Zhengyu Zhao
Hanwei Zhang
Renjue Li
R. Sicre
Laurent Amsaleg
Michael Backes
AAML
32
20
0
17 Nov 2022
Universal Distributional Decision-based Black-box Adversarial Attack
  with Reinforcement Learning
Universal Distributional Decision-based Black-box Adversarial Attack with Reinforcement Learning
Yiran Huang
Yexu Zhou
Michael Hefenbrock
T. Riedel
Likun Fang
Michael Beigl
AAML
24
3
0
15 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks
An Adversarial Robustness Perspective on the Topology of Neural Networks
Morgane Goibert
Thomas Ricatte
Elvis Dohmatob
AAML
24
2
0
04 Nov 2022
Ares: A System-Oriented Wargame Framework for Adversarial ML
Ares: A System-Oriented Wargame Framework for Adversarial ML
Farhan Ahmed
Pratik Vaishnavi
Kevin Eykholt
Amir Rahmati
AAML
25
7
0
24 Oct 2022
Emerging Threats in Deep Learning-Based Autonomous Driving: A
  Comprehensive Survey
Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Survey
Huiyun Cao
Wenlong Zou
Yinkun Wang
Ting Song
Mengjun Liu
AAML
56
5
0
19 Oct 2022
Is Face Recognition Safe from Realizable Attacks?
Is Face Recognition Safe from Realizable Attacks?
Sanjay Saha
Terence Sim
CVBM
AAML
27
3
0
15 Oct 2022
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face
  Recognition
Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition
Shuai Jia
Bangjie Yin
Taiping Yao
Shouhong Ding
Chunhua Shen
Xiaokang Yang
Chao Ma
AAML
CVBM
34
49
0
13 Oct 2022
Adversarial Attack Against Image-Based Localization Neural Networks
Adversarial Attack Against Image-Based Localization Neural Networks
Meir Brand
I. Naeh
Daniel Teitelman
AAML
47
0
0
11 Oct 2022
Towards Understanding and Boosting Adversarial Transferability from a
  Distribution Perspective
Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective
Yao Zhu
YueFeng Chen
Xiaodan Li
Kejiang Chen
Yuan He
Xiang Tian
Bo Zheng
Yao-wu Chen
Qingming Huang
AAML
33
58
0
09 Oct 2022
DeltaBound Attack: Efficient decision-based attack in low queries regime
DeltaBound Attack: Efficient decision-based attack in low queries regime
L. Rossi
AAML
22
0
0
01 Oct 2022
Learning Robust Kernel Ensembles with Kernel Average Pooling
Learning Robust Kernel Ensembles with Kernel Average Pooling
P. Bashivan
Adam Ibrahim
Amirozhan Dehghani
Yifei Ren
OOD
24
5
0
30 Sep 2022
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Unrestricted Black-box Adversarial Attack Using GAN with Limited Queries
Dongbin Na
Sangwoo Ji
Jong Kim
AAML
35
17
0
24 Aug 2022
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps
Mohammadreza Amirian
Friedhelm Schwenker
Thilo Stadelmann
AAML
27
16
0
24 Aug 2022
Enhancing Targeted Attack Transferability via Diversified Weight Pruning
Enhancing Targeted Attack Transferability via Diversified Weight Pruning
Hung-Jui Wang
Yuehua Wu
Shang-Tse Chen
AAML
37
2
0
18 Aug 2022
Adversarial Pixel Restoration as a Pretext Task for Transferable
  Perturbations
Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations
H. Malik
Shahina Kunhimon
Muzammal Naseer
Salman Khan
Fahad Shahbaz Khan
AAML
35
8
0
18 Jul 2022
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Taha Belkhouja
Yan Yan
J. Doppa
AAML
AI4TS
32
25
0
09 Jul 2022
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and
  Theoretical Analysis
Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis
Taha Belkhouja
Yan Yan
J. Doppa
OOD
AI4TS
38
9
0
09 Jul 2022
An Empirical Study of Challenges in Converting Deep Learning Models
An Empirical Study of Challenges in Converting Deep Learning Models
Moses Openja
Amin Nikanjam
Ahmed Haj Yahmed
Foutse Khomh
Zhen Ming
Zhengyong Jiang
AAML
44
19
0
28 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
41
16
0
28 Jun 2022
RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition
  using a Mobile and Compact Printer
RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition using a Mobile and Compact Printer
Xiaoliang Liu
S. Furao
Jian Zhao
Changhai Nie
AAML
CVBM
36
5
0
25 Jun 2022
Detecting Adversarial Examples in Batches -- a geometrical approach
Detecting Adversarial Examples in Batches -- a geometrical approach
Danush Kumar Venkatesh
Peter Steinbach
AAML
11
2
0
17 Jun 2022
Boosting the Adversarial Transferability of Surrogate Models with Dark
  Knowledge
Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge
Dingcheng Yang
Zihao Xiao
Wenjian Yu
AAML
36
5
0
16 Jun 2022
Architectural Backdoors in Neural Networks
Architectural Backdoors in Neural Networks
Mikel Bober-Irizar
Ilia Shumailov
Yiren Zhao
Robert D. Mullins
Nicolas Papernot
AAML
28
23
0
15 Jun 2022
Wavelet Regularization Benefits Adversarial Training
Wavelet Regularization Benefits Adversarial Training
Jun Yan
Huilin Yin
Xiaoyang Deng
Zi-qin Zhao
Wancheng Ge
Hao Zhang
Gerhard Rigoll
AAML
24
2
0
08 Jun 2022
Towards Understanding and Mitigating Audio Adversarial Examples for
  Speaker Recognition
Towards Understanding and Mitigating Audio Adversarial Examples for Speaker Recognition
Guangke Chen
Zhe Zhao
Fu Song
Sen Chen
Lingling Fan
Feng Wang
Jiashui Wang
AAML
30
37
0
07 Jun 2022
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack
Zeyu Dai
Shengcai Liu
Jiaheng Zhang
Qing Li
AAML
37
11
0
04 Jun 2022
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box
  Score-Based Query Attacks
Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks
Sizhe Chen
Zhehao Huang
Qinghua Tao
Yingwen Wu
Cihang Xie
Xiaolin Huang
AAML
110
28
0
24 May 2022
Robust Representation via Dynamic Feature Aggregation
Robust Representation via Dynamic Feature Aggregation
Haozhe Liu
Haoqin Ji
Yuexiang Li
Nanjun He
Haoqian Wu
Feng Liu
Linlin Shen
Yefeng Zheng
AAML
OOD
37
3
0
16 May 2022
Automation Slicing and Testing for in-App Deep Learning Models
Automation Slicing and Testing for in-App Deep Learning Models
Hao Wu
Yuhang Gong
Xiaopeng Ke
Hanzhong Liang
Minghao Li
Fengyuan Xu
Yunxin Liu
Sheng Zhong
56
1
0
15 May 2022
Randomized Smoothing under Attack: How Good is it in Pratice?
Randomized Smoothing under Attack: How Good is it in Pratice?
Thibault Maho
Teddy Furon
Erwan Le Merrer
AAML
19
10
0
28 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
45
130
0
31 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
OOD
AAML
ObjD
54
72
0
26 Mar 2022
Improving the Transferability of Targeted Adversarial Examples through
  Object-Based Diverse Input
Improving the Transferability of Targeted Adversarial Examples through Object-Based Diverse Input
Junyoung Byun
Seungju Cho
Myung-Joon Kwon
Heeseon Kim
Changick Kim
AAML
DiffM
29
68
0
17 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
AAML
MLAU
19
25
0
16 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
53
10
0
09 Mar 2022
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation
Practical No-box Adversarial Attacks with Training-free Hybrid Image Transformation
Qilong Zhang
Chaoning Zhang
Chaoning Zhang
Chaoqun Li
Xuanhan Wang
Jingkuan Song
Lianli Gao
AAML
41
21
0
09 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
21
67
0
08 Mar 2022
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art
P. Williams
Ke Li
AAML
27
2
0
07 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors
Adversarial robustness of sparse local Lipschitz predictors
Ramchandran Muthukumar
Jeremias Sulam
AAML
34
13
0
26 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
29
6
0
15 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models
Holistic Adversarial Robustness of Deep Learning Models
Pin-Yu Chen
Sijia Liu
AAML
54
16
0
15 Feb 2022
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint
  Ensembles
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles
Ashish Hooda
Neal Mangaokar
Ryan Feng
Kassem Fawaz
S. Jha
Atul Prakash
35
11
0
11 Feb 2022
Query Efficient Decision Based Sparse Attacks Against Black-Box Deep
  Learning Models
Query Efficient Decision Based Sparse Attacks Against Black-Box Deep Learning Models
Viet Vo
Ehsan Abbasnejad
Damith C. Ranasinghe
AAML
42
14
0
31 Jan 2022
Boundary Defense Against Black-box Adversarial Attacks
Boundary Defense Against Black-box Adversarial Attacks
Manjushree B. Aithal
Xiaohua Li
AAML
28
6
0
31 Jan 2022
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