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Minimally distorted Adversarial Examples with a Fast Adaptive Boundary
  Attack

Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack

3 July 2019
Francesco Croce
Matthias Hein
    AAML
ArXivPDFHTML

Papers citing "Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack"

50 / 87 papers shown
Title
Cert-SSB: Toward Certified Sample-Specific Backdoor Defense
Cert-SSB: Toward Certified Sample-Specific Backdoor Defense
Ting Qiao
Y. Wang
Xing Liu
Sixing Wu
Jianbing Li
Yiming Li
AAML
SILM
66
0
0
30 Apr 2025
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models
X. Jia
Sensen Gao
Simeng Qin
Ke Ma
X. Li
Yihao Huang
Wei Dong
Yang Liu
Xiaochun Cao
AAML
VLM
60
0
0
17 Mar 2025
Nearshore Underwater Target Detection Meets UAV-borne Hyperspectral Remote Sensing: A Novel Hybrid-level Contrastive Learning Framework and Benchmark Dataset
Nearshore Underwater Target Detection Meets UAV-borne Hyperspectral Remote Sensing: A Novel Hybrid-level Contrastive Learning Framework and Benchmark Dataset
Jiahao Qi
Chuanhong Zhou
Xingyue Liu
Chen Chen
Dehui Zhu
Kangcheng Bin
Ping Zhong
74
0
0
21 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
62
0
0
20 Feb 2025
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo
Cheng Gong
Xi Victoria Lin
Fei Liu
Zhichao Lu
Qingfu Zhang
Zhenkun Wang
AAML
45
0
0
13 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
37
0
0
31 Dec 2024
RobustBlack: Challenging Black-Box Adversarial Attacks on State-of-the-Art Defenses
RobustBlack: Challenging Black-Box Adversarial Attacks on State-of-the-Art Defenses
Mohamed Djilani
Salah Ghamizi
Maxime Cordy
43
0
0
31 Dec 2024
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks
Yong Xie
Weijie Zheng
Hanxun Huang
Guangnan Ye
Xingjun Ma
AAML
72
1
0
20 Nov 2024
Natural Language Induced Adversarial Images
Natural Language Induced Adversarial Images
Xiaopei Zhu
Peiyang Xu
Guanning Zeng
Yingpeng Dong
Xiaolin Hu
AAML
28
0
0
11 Oct 2024
Accurate Forgetting for All-in-One Image Restoration Model
Accurate Forgetting for All-in-One Image Restoration Model
Xin Su
Zhuoran Zheng
CLL
26
1
0
01 Sep 2024
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness
Kejia Zhang
Juanjuan Weng
Yuanzheng Cai
Zhiming Luo
Shaozi Li
AAML
59
0
0
04 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
36
0
0
26 Jun 2024
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing
  Adversarial Robustness
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness
Kejia Zhang
Juanjuan Weng
Junwei Wu
Guoqing Yang
Shaozi Li
Zhiming Luo
AAML
38
1
0
17 Jun 2024
Improving Adversarial Robustness via Decoupled Visual Representation
  Masking
Improving Adversarial Robustness via Decoupled Visual Representation Masking
Decheng Liu
Tao Chen
Chunlei Peng
Nannan Wang
Ruimin Hu
Xinbo Gao
AAML
40
1
0
16 Jun 2024
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
Antonio Emanuele Cinà
Jérôme Rony
Maura Pintor
Luca Demetrio
Ambra Demontis
Battista Biggio
Ismail Ben Ayed
Fabio Roli
ELM
AAML
SILM
44
6
0
30 Apr 2024
Struggle with Adversarial Defense? Try Diffusion
Struggle with Adversarial Defense? Try Diffusion
Yujie Li
Yanbin Wang
Haitao Xu
Bin Liu
Jianguo Sun
Zhenhao Guo
Wenrui Ma
DiffM
27
1
0
12 Apr 2024
Theoretical Understanding of Learning from Adversarial Perturbations
Theoretical Understanding of Learning from Adversarial Perturbations
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
31
1
0
16 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
28
6
0
11 Feb 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off
  in Adversarial Training
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda
Bahram Zonooz
Elahe Arani
AAML
28
2
0
26 Jan 2024
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
Xiaoyun Xu
Shujian Yu
Jingzheng Wu
S. Picek
AAML
35
0
0
08 Dec 2023
Indirect Gradient Matching for Adversarial Robust Distillation
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee
Seungju Cho
Changick Kim
AAML
FedML
48
2
0
06 Dec 2023
Fast Certification of Vision-Language Models Using Incremental
  Randomized Smoothing
Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing
Ashutosh Nirala
Ameya Joshi
Chinmay Hegde
S Sarkar
VLM
30
0
0
15 Nov 2023
On The Relationship Between Universal Adversarial Attacks And Sparse
  Representations
On The Relationship Between Universal Adversarial Attacks And Sparse Representations
Dana Weitzner
Raja Giryes
AAML
24
0
0
14 Nov 2023
Purify++: Improving Diffusion-Purification with Advanced Diffusion
  Models and Control of Randomness
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness
Boya Zhang
Weijian Luo
Zhihua Zhang
29
10
0
28 Oct 2023
Assessing Robustness via Score-Based Adversarial Image Generation
Assessing Robustness via Score-Based Adversarial Image Generation
Marcel Kollovieh
Lukas Gosch
Yan Scholten
Marten Lienen
Leo Schwinn
Stephan Günnemann
DiffM
35
4
0
06 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
Mahyar Fazlyab
Taha Entesari
Aniket Roy
Ramalingam Chellappa
AAML
16
11
0
29 Sep 2023
Group Orthogonalization Regularization For Vision Models Adaptation and
  Robustness
Group Orthogonalization Regularization For Vision Models Adaptation and Robustness
Yoav Kurtz
Noga Bar
Raja Giryes
24
0
0
16 Jun 2023
On the Importance of Backbone to the Adversarial Robustness of Object Detectors
On the Importance of Backbone to the Adversarial Robustness of Object Detectors
Xiao-Li Li
Hang Chen
Xiaolin Hu
AAML
38
4
0
27 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks &
  Defenses
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses
Joana Cabral Costa
Tiago Roxo
Hugo Manuel Proença
Pedro R. M. Inácio
AAML
34
49
0
18 May 2023
Beyond Empirical Risk Minimization: Local Structure Preserving
  Regularization for Improving Adversarial Robustness
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness
Wei Wei
Jiahuan Zhou
Yingying Wu
AAML
13
0
0
29 Mar 2023
CAT:Collaborative Adversarial Training
CAT:Collaborative Adversarial Training
Xingbin Liu
Huafeng Kuang
Xianming Lin
Yongjian Wu
Rongrong Ji
AAML
17
4
0
27 Mar 2023
An Extended Study of Human-like Behavior under Adversarial Training
An Extended Study of Human-like Behavior under Adversarial Training
Paul Gavrikov
J. Keuper
M. Keuper
AAML
28
9
0
22 Mar 2023
Randomized Adversarial Training via Taylor Expansion
Randomized Adversarial Training via Taylor Expansion
Gao Jin
Xinping Yi
Dengyu Wu
Ronghui Mu
Xiaowei Huang
AAML
36
34
0
19 Mar 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive
  Smoothing
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing
Yatong Bai
Brendon G. Anderson
Aerin Kim
Somayeh Sojoudi
AAML
28
18
0
29 Jan 2023
Phase-shifted Adversarial Training
Phase-shifted Adversarial Training
Yeachan Kim
Seongyeon Kim
Ihyeok Seo
Bonggun Shin
AAML
OOD
24
0
0
12 Jan 2023
ExploreADV: Towards exploratory attack for Neural Networks
ExploreADV: Towards exploratory attack for Neural Networks
Tianzuo Luo
Yuyi Zhong
S. Khoo
AAML
22
1
0
01 Jan 2023
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Nikolaos Antoniou
Efthymios Georgiou
Alexandros Potamianos
AAML
27
5
0
15 Dec 2022
Improving Adversarial Robustness with Self-Paced Hard-Class Pair
  Reweighting
Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting
Peng-Fei Hou
Jie Han
Xingyu Li
AAML
OOD
16
11
0
26 Oct 2022
Scaling Adversarial Training to Large Perturbation Bounds
Scaling Adversarial Training to Large Perturbation Bounds
Sravanti Addepalli
Samyak Jain
Gaurang Sriramanan
R. Venkatesh Babu
AAML
25
22
0
18 Oct 2022
When Adversarial Training Meets Vision Transformers: Recipes from
  Training to Architecture
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Yi Mo
Dongxian Wu
Yifei Wang
Yiwen Guo
Yisen Wang
ViT
37
52
0
14 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin
  Regularization
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization
Ziquan Liu
Antoni B. Chan
AAML
25
5
0
11 Oct 2022
Strength-Adaptive Adversarial Training
Strength-Adaptive Adversarial Training
Chaojian Yu
Dawei Zhou
Li Shen
Jun Yu
Bo Han
Mingming Gong
Nannan Wang
Tongliang Liu
OOD
17
2
0
04 Oct 2022
Inducing Data Amplification Using Auxiliary Datasets in Adversarial
  Training
Inducing Data Amplification Using Auxiliary Datasets in Adversarial Training
Saehyung Lee
Hyungyu Lee
AAML
22
2
0
27 Sep 2022
A Light Recipe to Train Robust Vision Transformers
A Light Recipe to Train Robust Vision Transformers
Edoardo Debenedetti
Vikash Sehwag
Prateek Mittal
ViT
26
68
0
15 Sep 2022
On the Transferability of Adversarial Examples between Encrypted Models
On the Transferability of Adversarial Examples between Encrypted Models
Miki Tanaka
Isao Echizen
Hitoshi Kiya
SILM
26
4
0
07 Sep 2022
Bag of Tricks for FGSM Adversarial Training
Bag of Tricks for FGSM Adversarial Training
Zichao Li
Li Liu
Zeyu Wang
Yuyin Zhou
Cihang Xie
AAML
23
6
0
06 Sep 2022
Membership Inference Attacks via Adversarial Examples
Membership Inference Attacks via Adversarial Examples
Hamid Jalalzai
Elie Kadoche
Rémi Leluc
Vincent Plassier
AAML
FedML
MIACV
27
7
0
27 Jul 2022
Contrastive Self-Supervised Learning Leads to Higher Adversarial
  Susceptibility
Contrastive Self-Supervised Learning Leads to Higher Adversarial Susceptibility
Rohit Gupta
Naveed Akhtar
Ajmal Saeed Mian
M. Shah
AAML
SSL
21
5
0
22 Jul 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
36
16
0
28 Jun 2022
Building Robust Ensembles via Margin Boosting
Building Robust Ensembles via Margin Boosting
Dinghuai Zhang
Hongyang R. Zhang
Aaron Courville
Yoshua Bengio
Pradeep Ravikumar
A. Suggala
AAML
UQCV
37
15
0
07 Jun 2022
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