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DeepFool: a simple and accurate method to fool deep neural networks

DeepFool: a simple and accurate method to fool deep neural networks

14 November 2015
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
    AAML
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Papers citing "DeepFool: a simple and accurate method to fool deep neural networks"

50 / 824 papers shown
Title
Security through the Eyes of AI: How Visualization is Shaping Malware Detection
Security through the Eyes of AI: How Visualization is Shaping Malware Detection
Matteo Brosolo
A. Aazami
R. Agarwal
M. Prabhakaran
S. Nicolazzo
Antonino Nocera
V. P.
AAML
37
0
0
12 May 2025
Crafting Physical Adversarial Examples by Combining Differentiable and Physically Based Renders
Crafting Physical Adversarial Examples by Combining Differentiable and Physically Based Renders
Yuqiu Liu
Huanqian Yan
Xiaopei Zhu
Xiaolin Hu
L. Tang
Hang Su
Chen Lv
34
0
0
07 May 2025
Data-Driven Falsification of Cyber-Physical Systems
Data-Driven Falsification of Cyber-Physical Systems
Atanu Kundu
Sauvik Gon
Rajarshi Ray
AAML
AI4CE
41
3
0
06 May 2025
Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability
Constrained Network Adversarial Attacks: Validity, Robustness, and Transferability
Anass Grini
Oumaima Taheri
Btissam El Khamlichi
Amal El Fallah-Seghrouchni
AAML
49
0
0
02 May 2025
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
What's Pulling the Strings? Evaluating Integrity and Attribution in AI Training and Inference through Concept Shift
Jiamin Chang
Yiming Li
Hammond Pearce
Ruoxi Sun
Bo-wen Li
Minhui Xue
38
0
0
28 Apr 2025
Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models
Examining the Impact of Optical Aberrations to Image Classification and Object Detection Models
Patrick Müller
Alexander Braun
M. Keuper
59
0
0
25 Apr 2025
DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks
DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks
Jing Chen
Onat Gungor
Zhengli Shang
Elvin Li
T. Rosing
AAML
42
0
0
17 Apr 2025
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
Jialei Song
Xingquan Zuo
Feiyang Wang
Hai Huang
Tianle Zhang
AAML
139
0
0
16 Apr 2025
Human Aligned Compression for Robust Models
Human Aligned Compression for Robust Models
Samuel Räber
Andreas Plesner
Till Aczél
Roger Wattenhofer
AAML
42
0
0
16 Apr 2025
From Visual Explanations to Counterfactual Explanations with Latent Diffusion
From Visual Explanations to Counterfactual Explanations with Latent Diffusion
Tung Luu
Nam Le
Duc Le
Bac Le
DiffM
AAML
FAtt
50
0
0
12 Apr 2025
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models
Yoojin Jung
Byung Cheol Song
AAML
VLM
MQ
41
0
0
07 Apr 2025
GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
GSBAK^KK: toptoptop-KKK Geometric Score-based Black-box Attack
Md. Farhamdur Reza
Richeng Jin
Tianfu Wu
H. Dai
AAML
47
0
0
17 Mar 2025
Attackers Can Do Better: Over- and Understated Factors of Model Stealing Attacks
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
AAML
49
0
0
08 Mar 2025
Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior
Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior
Chanhui Lee
Yeonghwan Song
Jeany Son
AAML
192
0
0
28 Feb 2025
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Emanuele Ballarin
A. Ansuini
Luca Bortolussi
AAML
64
0
0
20 Feb 2025
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
Amy Rafferty
Rishi Ramaesh
Ajitha Rajan
MedIm
AAML
56
0
0
04 Feb 2025
On the uncertainty principle of neural networks
On the uncertainty principle of neural networks
Jun-Jie Zhang
Dong-xiao Zhang
Jian-Nan Chen
L. Pang
Deyu Meng
57
2
0
17 Jan 2025
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Olukorede Fakorede
Modeste Atsague
Jin Tian
AAML
42
0
0
31 Dec 2024
UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models
UIBDiffusion: Universal Imperceptible Backdoor Attack for Diffusion Models
Yuning Han
Bingyin Zhao
Rui Chu
Feng Luo
Biplab Sikdar
Yingjie Lao
DiffM
AAML
95
1
0
16 Dec 2024
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training
Tejaswini Medi
Steffen Jung
M. Keuper
AAML
44
3
0
30 Oct 2024
Efficient Optimization Algorithms for Linear Adversarial Training
Efficient Optimization Algorithms for Linear Adversarial Training
Antônio H. Ribeiro
Thomas B. Schon
Dave Zahariah
Francis Bach
AAML
55
1
0
16 Oct 2024
Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture
Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture
Sajad Movahedi
Antonio Orvieto
Seyed-Mohsen Moosavi-Dezfooli
AI4CE
AAML
192
0
0
15 Oct 2024
A Brain-Inspired Regularizer for Adversarial Robustness
A Brain-Inspired Regularizer for Adversarial Robustness
Elie Attias
Cengiz Pehlevan
D. Obeid
AAML
OOD
20
0
0
04 Oct 2024
On Using Certified Training towards Empirical Robustness
On Using Certified Training towards Empirical Robustness
Alessandro De Palma
Serge Durand
Zakaria Chihani
François Terrier
Caterina Urban
OOD
AAML
38
1
0
02 Oct 2024
The Roles of Generative Artificial Intelligence in Internet of Electric
  Vehicles
The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles
Hanwen Zhang
Dusit Niyato
Wei Zhang
Changyuan Zhao
Hongyang Du
Abbas Jamalipour
Sumei Sun
Yiyang Pei
AI4CE
44
2
0
24 Sep 2024
A Cost-Aware Approach to Adversarial Robustness in Neural Networks
A Cost-Aware Approach to Adversarial Robustness in Neural Networks
Charles Meyers
Mohammad Reza Saleh Sedghpour
Tommy Löfstedt
Erik Elmroth
OOD
AAML
33
0
0
11 Sep 2024
Input Space Mode Connectivity in Deep Neural Networks
Input Space Mode Connectivity in Deep Neural Networks
Jakub Vrabel
Ori Shem-Ur
Yaron Oz
David Krueger
58
1
0
09 Sep 2024
Learning to Learn Transferable Generative Attack for Person Re-Identification
Learning to Learn Transferable Generative Attack for Person Re-Identification
Yuan Bian
Min Liu
Xueping Wang
Yunfeng Ma
Yaonan Wang
AAML
OOD
68
1
0
06 Sep 2024
ADBM: Adversarial diffusion bridge model for reliable adversarial purification
ADBM: Adversarial diffusion bridge model for reliable adversarial purification
Xiao-Li Li
Wenxuan Sun
Huanran Chen
Qiongxiu Li
Yining Liu
Yingzhe He
Jie Shi
Xiaolin Hu
AAML
63
8
0
01 Aug 2024
Backdoor Attacks against Image-to-Image Networks
Backdoor Attacks against Image-to-Image Networks
Wenbo Jiang
Hongwei Li
Jiaming He
Rui Zhang
Guowen Xu
Tianwei Zhang
Rongxing Lu
AAML
45
3
0
15 Jul 2024
Self-Supervised Representation Learning for Adversarial Attack Detection
Self-Supervised Representation Learning for Adversarial Attack Detection
Yi Li
Plamen Angelov
N. Suri
SSL
AAML
33
3
0
05 Jul 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in
  Deep Robust Classifiers
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
Jonas Ngnawé
Sabyasachi Sahoo
Y. Pequignot
Frédéric Precioso
Christian Gagné
AAML
42
0
0
26 Jun 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
Peter Lorenz
Mario Fernandez
Jens Müller
Ullrich Kothe
AAML
78
1
0
21 Jun 2024
Obfuscating IoT Device Scanning Activity via Adversarial Example
  Generation
Obfuscating IoT Device Scanning Activity via Adversarial Example Generation
Haocong Li
Yaxin Zhang
Long Cheng
Wenjia Niu
Haining Wang
Qiang Li
AAML
41
0
0
17 Jun 2024
One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models
One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models
Hao Fang
Jiawei Kong
Wenbo Yu
Bin Chen
Jiawei Li
Hao Wu
Ke Xu
Ke Xu
AAML
VLM
40
13
0
08 Jun 2024
HOLMES: to Detect Adversarial Examples with Multiple Detectors
HOLMES: to Detect Adversarial Examples with Multiple Detectors
Jing Wen
AAML
41
0
0
30 May 2024
OSLO: One-Shot Label-Only Membership Inference Attacks
OSLO: One-Shot Label-Only Membership Inference Attacks
Yuefeng Peng
Jaechul Roh
Subhransu Maji
Amir Houmansadr
44
0
0
27 May 2024
Probing Human Visual Robustness with Neurally-Guided Deep Neural Networks
Probing Human Visual Robustness with Neurally-Guided Deep Neural Networks
Zhenan Shao
Linjian Ma
Yiqing Zhou
Yibo Jacky Zhang
Sanmi Koyejo
Bo Li
Diane M. Beck
AAML
51
3
0
04 May 2024
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
Antonio Emanuele Cinà
Jérôme Rony
Maura Pintor
Christian Scano
Ambra Demontis
Battista Biggio
Ismail Ben Ayed
Fabio Roli
ELM
AAML
SILM
44
8
0
30 Apr 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
A Survey of Neural Network Robustness Assessment in Image Recognition
Jie Wang
Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
Junda Zhu
Jingyu Liu
AAML
30
3
0
12 Apr 2024
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset
  Distillation
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset Distillation
Yifan Wu
Jiawei Du
Ping Liu
Yuewei Lin
Wenqing Cheng
Wei-ping Xu
DD
AAML
40
5
0
20 Mar 2024
Robust Overfitting Does Matter: Test-Time Adversarial Purification With
  FGSM
Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSM
Linyu Tang
Lei Zhang
AAML
35
3
0
18 Mar 2024
Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A
  Pilot Study
Benchmarking Zero-Shot Robustness of Multimodal Foundation Models: A Pilot Study
Chenguang Wang
Ruoxi Jia
Xin Liu
Dawn Song
VLM
29
7
0
15 Mar 2024
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Eric Xue
Yijiang Li
Haoyang Liu
Yifan Shen
Haohan Wang
Haohan Wang
DD
61
8
0
15 Mar 2024
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
Haoyang Liu
Aditya Singh
Yijiang Li
Haohan Wang
AAML
ViT
39
1
0
15 Mar 2024
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks
Edgar Medina
Leyong Loh
AAML
32
0
0
07 Mar 2024
Theoretical Understanding of Learning from Adversarial Perturbations
Theoretical Understanding of Learning from Adversarial Perturbations
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
41
1
0
16 Feb 2024
NeuralSentinel: Safeguarding Neural Network Reliability and
  Trustworthiness
NeuralSentinel: Safeguarding Neural Network Reliability and Trustworthiness
Xabier Echeberria-Barrio
Mikel Gorricho
Selene Valencia
Francesco Zola
AAML
26
1
0
12 Feb 2024
Understanding Deep Learning defenses Against Adversarial Examples
  Through Visualizations for Dynamic Risk Assessment
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment
Xabier Echeberria-Barrio
Amaia Gil-Lerchundi
Jon Egana-Zubia
Raul Orduna Urrutia
AAML
32
6
0
12 Feb 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially
  Robust Defense
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense
Ryota Iijima
Sayaka Shiota
Hitoshi Kiya
36
6
0
11 Feb 2024
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