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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

29 December 2021
Futa Waseda
Sosuke Nishikawa
Trung-Nghia Le
H. Nguyen
Isao Echizen
    SILM
ArXivPDFHTML

Papers citing "Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently"

12 / 12 papers shown
Title
Clean Label Attacks against SLU Systems
Clean Label Attacks against SLU Systems
Henry Li Xinyuan
Sonal Joshi
Thomas Thebaud
Jesus Villalba
Najim Dehak
Sanjeev Khudanpur
AAML
32
0
0
13 Sep 2024
As Firm As Their Foundations: Can open-sourced foundation models be used
  to create adversarial examples for downstream tasks?
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?
Anjun Hu
Jindong Gu
Francesco Pinto
Konstantinos Kamnitsas
Philip H. S. Torr
AAML
SILM
32
5
0
19 Mar 2024
SA-Attack: Improving Adversarial Transferability of Vision-Language
  Pre-training Models via Self-Augmentation
SA-Attack: Improving Adversarial Transferability of Vision-Language Pre-training Models via Self-Augmentation
Bangyan He
Xiaojun Jia
Siyuan Liang
Tianrui Lou
Yang Liu
Xiaochun Cao
AAML
VLM
24
23
0
08 Dec 2023
OT-Attack: Enhancing Adversarial Transferability of Vision-Language
  Models via Optimal Transport Optimization
OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization
Dongchen Han
Xiaojun Jia
Yang Bai
Jindong Gu
Yang Liu
Xiaochun Cao
VLM
30
22
0
07 Dec 2023
Improving Adversarial Transferability via Model Alignment
Improving Adversarial Transferability via Model Alignment
A. Ma
Amir-massoud Farahmand
Yangchen Pan
Philip H. S. Torr
Jindong Gu
AAML
28
5
0
30 Nov 2023
A Survey on Transferability of Adversarial Examples across Deep Neural
  Networks
A Survey on Transferability of Adversarial Examples across Deep Neural Networks
Jindong Gu
Xiaojun Jia
Pau de Jorge
Wenqain Yu
Xinwei Liu
...
Anjun Hu
Ashkan Khakzar
Zhijiang Li
Xiaochun Cao
Philip H. S. Torr
AAML
29
26
0
26 Oct 2023
On the Computational Entanglement of Distant Features in Adversarial
  Machine Learning
On the Computational Entanglement of Distant Features in Adversarial Machine Learning
Yen-Lung Lai
Xingbo Dong
Zhe Jin
AAML
11
0
0
27 Sep 2023
Common Knowledge Learning for Generating Transferable Adversarial
  Examples
Common Knowledge Learning for Generating Transferable Adversarial Examples
Rui Yang
Yuanfang Guo
Junfu Wang
Jiantao Zhou
Yun-an Wang
AAML
13
0
0
01 Jul 2023
Reliable Evaluation of Adversarial Transferability
Reliable Evaluation of Adversarial Transferability
Wenqian Yu
Jindong Gu
Zhijiang Li
Philip H. S. Torr
AAML
27
8
0
14 Jun 2023
Adversarial-Aware Deep Learning System based on a Secondary Classical
  Machine Learning Verification Approach
Adversarial-Aware Deep Learning System based on a Secondary Classical Machine Learning Verification Approach
Mohammed Alkhowaiter
Hisham A. Kholidy
Mnassar Alyami
Abdulmajeed Alghamdi
C. Zou
AAML
19
8
0
01 Jun 2023
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
24
1
0
20 Oct 2022
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
281
5,833
0
08 Jul 2016
1