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The Space of Transferable Adversarial Examples

The Space of Transferable Adversarial Examples

11 April 2017
Florian Tramèr
Nicolas Papernot
Ian Goodfellow
Dan Boneh
Patrick McDaniel
    AAML
    SILM
ArXivPDFHTML

Papers citing "The Space of Transferable Adversarial Examples"

50 / 117 papers shown
Title
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
Hanxun Huang
Sarah Monazam Erfani
Yige Li
Xingjun Ma
James Bailey
AAML
55
0
0
08 May 2025
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
Xiao Yang
Gaolei Li
Jianhua Li
AAML
AI4CE
56
1
0
08 Jan 2025
Understanding Model Ensemble in Transferable Adversarial Attack
Understanding Model Ensemble in Transferable Adversarial Attack
Wei Yao
Zeliang Zhang
Huayi Tang
Yong Liu
33
2
0
09 Oct 2024
PubDef: Defending Against Transfer Attacks From Public Models
PubDef: Defending Against Transfer Attacks From Public Models
Chawin Sitawarin
Jaewon Chang
David Huang
Wesson Altoyan
David Wagner
AAML
39
6
0
26 Oct 2023
A Survey of Robustness and Safety of 2D and 3D Deep Learning Models
  Against Adversarial Attacks
A Survey of Robustness and Safety of 2D and 3D Deep Learning Models Against Adversarial Attacks
Yanjie Li
Bin Xie
Songtao Guo
Yuanyuan Yang
Bin Xiao
AAML
40
16
0
01 Oct 2023
Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake
  Detection
Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake Detection
Weijie Wang
Zhengyu Zhao
N. Sebe
Bruno Lepri
AAML
41
2
0
03 Sep 2023
Doubly Robust Instance-Reweighted Adversarial Training
Doubly Robust Instance-Reweighted Adversarial Training
Daouda Sow
Sen-Fon Lin
Zhangyang Wang
Yitao Liang
AAML
OOD
33
2
0
01 Aug 2023
A LLM Assisted Exploitation of AI-Guardian
A LLM Assisted Exploitation of AI-Guardian
Nicholas Carlini
ELM
SILM
24
15
0
20 Jul 2023
Eigenpatches -- Adversarial Patches from Principal Components
Eigenpatches -- Adversarial Patches from Principal Components
Jens Bayer
S. Becker
David Munch
Michael Arens
AAML
38
1
0
19 Jun 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
52
51
0
18 May 2023
Differentially Private Attention Computation
Differentially Private Attention Computation
Yeqi Gao
Zhao Song
Xin Yang
55
21
0
08 May 2023
AdPE: Adversarial Positional Embeddings for Pretraining Vision
  Transformers via MAE+
AdPE: Adversarial Positional Embeddings for Pretraining Vision Transformers via MAE+
Tianlin Li
Ying Wang
Ziwei Xuan
Guo-Jun Qi
ViT
45
3
0
14 Mar 2023
Boosting Adversarial Attacks by Leveraging Decision Boundary Information
Boosting Adversarial Attacks by Leveraging Decision Boundary Information
Boheng Zeng
LianLi Gao
Qilong Zhang
Chaoqun Li
JingKuan Song
Shuaiqi Jing
AAML
22
2
0
10 Mar 2023
Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the
  Generation of Adversarial Examples
Immune Defense: A Novel Adversarial Defense Mechanism for Preventing the Generation of Adversarial Examples
Jinwei Wang
Hao Wu
Haihua Wang
Jiawei Zhang
X. Luo
Bin Ma
AAML
28
0
0
08 Mar 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
34
27
0
01 Jan 2023
Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted
  Attacks
Minimizing Maximum Model Discrepancy for Transferable Black-box Targeted Attacks
Anqi Zhao
Tong Chu
Yahao Liu
Wen Li
Jingjing Li
Lixin Duan
AAML
28
16
0
18 Dec 2022
REAP: A Large-Scale Realistic Adversarial Patch Benchmark
REAP: A Large-Scale Realistic Adversarial Patch Benchmark
Nabeel Hingun
Chawin Sitawarin
Jerry Li
David Wagner
AAML
31
14
0
12 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
Robust Smart Home Face Recognition under Starving Federated Data
Robust Smart Home Face Recognition under Starving Federated Data
Jaechul Roh
Yajun Fang
FedML
CVBM
AAML
26
0
0
10 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
13
2
0
04 Nov 2022
Similarity of Neural Architectures using Adversarial Attack
  Transferability
Similarity of Neural Architectures using Adversarial Attack Transferability
Jaehui Hwang
Dongyoon Han
Byeongho Heo
Song Park
Sanghyuk Chun
Jong-Seok Lee
AAML
37
1
0
20 Oct 2022
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
Khoa D. Doan
Yingjie Lao
Ping Li
34
40
0
17 Oct 2022
A Black-Box Attack on Optical Character Recognition Systems
A Black-Box Attack on Optical Character Recognition Systems
Samet Bayram
Kenneth Barner
AAML
17
5
0
30 Aug 2022
LGV: Boosting Adversarial Example Transferability from Large Geometric
  Vicinity
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity
Martin Gubri
Maxime Cordy
Mike Papadakis
Yves Le Traon
Koushik Sen
AAML
35
51
0
26 Jul 2022
Decorrelative Network Architecture for Robust Electrocardiogram
  Classification
Decorrelative Network Architecture for Robust Electrocardiogram Classification
Christopher Wiedeman
Ge Wang
OOD
13
2
0
19 Jul 2022
How many perturbations break this model? Evaluating robustness beyond
  adversarial accuracy
How many perturbations break this model? Evaluating robustness beyond adversarial accuracy
R. Olivier
Bhiksha Raj
AAML
34
5
0
08 Jul 2022
On the Role of Generalization in Transferability of Adversarial Examples
On the Role of Generalization in Transferability of Adversarial Examples
Yilin Wang
Farzan Farnia
AAML
24
10
0
18 Jun 2022
Meet You Halfway: Explaining Deep Learning Mysteries
Meet You Halfway: Explaining Deep Learning Mysteries
Oriel BenShmuel
AAML
FedML
FAtt
OOD
30
0
0
09 Jun 2022
AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker
  Recognition Systems
AS2T: Arbitrary Source-To-Target Adversarial Attack on Speaker Recognition Systems
Guangke Chen
Zhe Zhao
Fu Song
Sen Chen
Lingling Fan
Yang Liu
AAML
35
18
0
07 Jun 2022
On the reversibility of adversarial attacks
On the reversibility of adversarial attacks
C. Li
Ricardo Sánchez-Matilla
Ali Shahin Shamsabadi
Riccardo Mazzon
Andrea Cavallaro
AAML
19
2
0
01 Jun 2022
Subverting Fair Image Search with Generative Adversarial Perturbations
Subverting Fair Image Search with Generative Adversarial Perturbations
A. Ghosh
Matthew Jagielski
Chris L. Wilson
22
7
0
05 May 2022
Fingerprinting Deep Neural Networks Globally via Universal Adversarial
  Perturbations
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
Zirui Peng
Shaofeng Li
Guoxing Chen
Cheng Zhang
Haojin Zhu
Minhui Xue
AAML
FedML
31
66
0
17 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
29
11
0
11 Feb 2022
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
36
35
0
29 Dec 2021
Mutual Adversarial Training: Learning together is better than going
  alone
Mutual Adversarial Training: Learning together is better than going alone
Jiang-Long Liu
Chun Pong Lau
Hossein Souri
S. Feizi
Ramalingam Chellappa
OOD
AAML
48
24
0
09 Dec 2021
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial
  Domain Adaptation
Adv-4-Adv: Thwarting Changing Adversarial Perturbations via Adversarial Domain Adaptation
Tianyue Zheng
Zhe Chen
Shuya Ding
Chao Cai
Jun Luo
AAML
35
5
0
01 Dec 2021
Robust and Information-theoretically Safe Bias Classifier against
  Adversarial Attacks
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks
Lijia Yu
Xiao-Shan Gao
AAML
21
5
0
08 Nov 2021
Towards Evaluating the Robustness of Neural Networks Learned by
  Transduction
Towards Evaluating the Robustness of Neural Networks Learned by Transduction
Jiefeng Chen
Xi Wu
Yang Guo
Yingyu Liang
S. Jha
ELM
AAML
17
15
0
27 Oct 2021
Adversarial Robustness in Multi-Task Learning: Promises and Illusions
Adversarial Robustness in Multi-Task Learning: Promises and Illusions
Salah Ghamizi
Maxime Cordy
Mike Papadakis
Yves Le Traon
OOD
AAML
31
18
0
26 Oct 2021
Multi-concept adversarial attacks
Multi-concept adversarial attacks
Vibha Belavadi
Yan Zhou
Murat Kantarcioglu
B. Thuraisingham
AAML
35
0
0
19 Oct 2021
Demystifying the Transferability of Adversarial Attacks in Computer
  Networks
Demystifying the Transferability of Adversarial Attacks in Computer Networks
Ehsan Nowroozi
Yassine Mekdad
Mohammad Hajian Berenjestanaki
Mauro Conti
Abdeslam El Fergougui
AAML
42
32
0
09 Oct 2021
Adversarial Transfer Attacks With Unknown Data and Class Overlap
Adversarial Transfer Attacks With Unknown Data and Class Overlap
Luke E. Richards
A. Nguyen
Ryan Capps
Steven D. Forsythe
Cynthia Matuszek
Edward Raff
AAML
41
7
0
23 Sep 2021
Evolving Architectures with Gradient Misalignment toward Low Adversarial
  Transferability
Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferability
K. Operiano
W. Pora
H. Iba
Hiroshi Kera
AAML
29
1
0
13 Sep 2021
Disrupting Adversarial Transferability in Deep Neural Networks
Disrupting Adversarial Transferability in Deep Neural Networks
Christopher Wiedeman
Ge Wang
AAML
36
8
0
27 Aug 2021
SoK: How Robust is Image Classification Deep Neural Network
  Watermarking? (Extended Version)
SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version)
Nils Lukas
Edward Jiang
Xinda Li
Florian Kerschbaum
AAML
36
87
0
11 Aug 2021
On the Exploitability of Audio Machine Learning Pipelines to
  Surreptitious Adversarial Examples
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples
Adelin Travers
Lorna Licollari
Guanghan Wang
Varun Chandrasekaran
Adam Dziedzic
David Lie
Nicolas Papernot
AAML
33
3
0
03 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Mian
Navid Kardan
M. Shah
AAML
36
236
0
01 Aug 2021
GradDiv: Adversarial Robustness of Randomized Neural Networks via
  Gradient Diversity Regularization
GradDiv: Adversarial Robustness of Randomized Neural Networks via Gradient Diversity Regularization
Sungyoon Lee
Hoki Kim
Jaewook Lee
AAML
35
52
0
06 Jul 2021
Partial success in closing the gap between human and machine vision
Partial success in closing the gap between human and machine vision
Robert Geirhos
Kantharaju Narayanappa
Benjamin Mitzkus
Tizian Thieringer
Matthias Bethge
Felix Wichmann
Wieland Brendel
VLM
AAML
48
221
0
14 Jun 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for
  Enhanced Adversarial Robustness
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness
Yi Cai
Xuefei Ning
Huazhong Yang
Yu Wang
AAML
27
4
0
27 Mar 2021
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