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Guided Adversarial Attack for Evaluating and Enhancing Adversarial
  Defenses

Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses

30 November 2020
Gaurang Sriramanan
Sravanti Addepalli
Arya Baburaj
R. Venkatesh Babu
    AAML
ArXivPDFHTML

Papers citing "Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses"

19 / 19 papers shown
Title
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
FCGHunter: Towards Evaluating Robustness of Graph-Based Android Malware Detection
Shiwen Song
Xiaofei Xie
Ruitao Feng
Qi Guo
Sen Chen
AAML
45
0
0
28 Apr 2025
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo
Cheng Gong
Xi Lin
Fei Liu
Zhichao Lu
Qingfu Zhang
Zhenkun Wang
AAML
45
0
0
13 Jan 2025
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Binghui Li
Yuanzhi Li
OOD
30
2
0
11 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
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
Improving Fast Adversarial Training with Prior-Guided Knowledge
Improving Fast Adversarial Training with Prior-Guided Knowledge
Xiaojun Jia
Yong Zhang
Xingxing Wei
Baoyuan Wu
Ke Ma
Jue Wang
Xiaochun Cao
AAML
26
26
0
01 Apr 2023
Randomized Adversarial Training via Taylor Expansion
Randomized Adversarial Training via Taylor Expansion
Gao Jin
Xinping Yi
Dengyu Wu
Ronghui Mu
Xiaowei Huang
AAML
41
34
0
19 Mar 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
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Alternating Objectives Generates Stronger PGD-Based Adversarial Attacks
Nikolaos Antoniou
Efthymios Georgiou
Alexandros Potamianos
AAML
29
5
0
15 Dec 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
33
22
0
18 Oct 2022
Complete Verification via Multi-Neuron Relaxation Guided
  Branch-and-Bound
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
Claudio Ferrari
Mark Niklas Muller
Nikola Jovanović
Martin Vechev
28
82
0
30 Apr 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
Tianyu Pang
Min-Bin Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
30
119
0
21 Feb 2022
Scale-Invariant Adversarial Attack for Evaluating and Enhancing
  Adversarial Defenses
Scale-Invariant Adversarial Attack for Evaluating and Enhancing Adversarial Defenses
Mengting Xu
Tao Zhang
Zhongnian Li
Daoqiang Zhang
AAML
30
1
0
29 Jan 2022
Subspace Adversarial Training
Subspace Adversarial Training
Tao Li
Yingwen Wu
Sizhe Chen
Kun Fang
Xiaolin Huang
AAML
OOD
41
56
0
24 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural
  Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
46
100
0
07 Oct 2021
Training Meta-Surrogate Model for Transferable Adversarial Attack
Training Meta-Surrogate Model for Transferable Adversarial Attack
Yunxiao Qin
Yuanhao Xiong
Jinfeng Yi
Cho-Jui Hsieh
AAML
15
18
0
05 Sep 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 Saeed Mian
Navid Kardan
M. Shah
AAML
26
235
0
01 Aug 2021
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,110
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
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