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Gray-box Adversarial Training

Gray-box Adversarial Training

6 August 2018
S. VivekB.
Konda Reddy Mopuri
R. Venkatesh Babu
    AAML
ArXiv (abs)PDFHTML

Papers citing "Gray-box Adversarial Training"

16 / 16 papers shown
Adversarial Training: A Survey
Adversarial Training: A Survey
Mengnan Zhao
Lihe Zhang
Jingwen Ye
Huchuan Lu
Baocai Yin
Xinchao Wang
AAML
310
12
0
19 Oct 2024
Low-Rank Adversarial PGD Attack
Low-Rank Adversarial PGD Attack
Dayana Savostianova
Emanuele Zangrando
Francesco Tudisco
AAML
267
4
0
16 Oct 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially
  Robust Defense
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust DefenseIEEE Access (IEEE Access), 2024
Ryota Iijima
Sayaka Shiota
Hitoshi Kiya
304
9
0
11 Feb 2024
OMG-ATTACK: Self-Supervised On-Manifold Generation of Transferable
  Evasion Attacks
OMG-ATTACK: Self-Supervised On-Manifold Generation of Transferable Evasion Attacks
Ofir Bar Tal
Adi Haviv
Amit H. Bermano
AAML
176
0
0
05 Oct 2023
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A
  Survey
Adversarial Attacks and Defenses on 3D Point Cloud Classification: A SurveyIEEE Access (IEEE Access), 2023
Hanieh Naderi
Ivan V. Bajić
3DPC
377
10
0
01 Jul 2023
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and
  Boosting Segmentation Robustness
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation RobustnessEuropean Conference on Computer Vision (ECCV), 2022
Jindong Gu
Hengshuang Zhao
Volker Tresp
Juil Sock
AAML
290
91
0
25 Jul 2022
A Tutorial on Adversarial Learning Attacks and Countermeasures
A Tutorial on Adversarial Learning Attacks and Countermeasures
Cato Pauling
Michael Gimson
Muhammed Qaid
Ahmad Kida
Basel Halak
AAML
206
12
0
21 Feb 2022
Random Walks for Adversarial Meshes
Random Walks for Adversarial MeshesInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022
Amir Belder
Gal Yefet
Ran Ben Izhak
A. Tal
AAML
189
2
0
15 Feb 2022
A Survey on Adversarial Attacks for Malware Analysis
A Survey on Adversarial Attacks for Malware AnalysisIEEE Access (IEEE Access), 2021
Kshitiz Aryal
Maanak Gupta
Mahmoud Abdelsalam
AAML
315
65
0
16 Nov 2021
Adversarial Attacks with Time-Scale Representations
Adversarial Attacks with Time-Scale Representations
Alberto Santamaria-Pang
Jia-dong Qiu
Aritra Chowdhury
James R. Kubricht
Peter Tu
Iyer Naresh
Nurali Virani
AAMLMLAU
137
0
0
26 Jul 2021
Towards a Robust and Trustworthy Machine Learning System Development: An
  Engineering Perspective
Towards a Robust and Trustworthy Machine Learning System Development: An Engineering PerspectiveJournal of Information Security and Applications (JISA), 2021
Pulei Xiong
Scott Buffett
Shahrear Iqbal
Philippe Lamontagne
M. Mamun
Heather Molyneaux
OOD
317
19
0
08 Jan 2021
Query-Free Adversarial Transfer via Undertrained Surrogates
Query-Free Adversarial Transfer via Undertrained Surrogates
Chris Miller
Soroush Vosoughi
AAML
125
0
0
01 Jul 2020
The Attacker's Perspective on Automatic Speaker Verification: An
  Overview
The Attacker's Perspective on Automatic Speaker Verification: An OverviewInterspeech (Interspeech), 2020
Rohan Kumar Das
Xiaohai Tian
Tomi Kinnunen
Haizhou Li
AAML
154
87
0
19 Apr 2020
Single-step Adversarial training with Dropout Scheduling
Single-step Adversarial training with Dropout SchedulingComputer Vision and Pattern Recognition (CVPR), 2020
S. VivekB.
R. Venkatesh Babu
OODAAML
136
79
0
18 Apr 2020
Generating Black-Box Adversarial Examples for Text Classifiers Using a
  Deep Reinforced Model
Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model
Prashanth Vijayaraghavan
D. Roy
AAML
113
39
0
17 Sep 2019
FDA: Feature Disruptive Attack
FDA: Feature Disruptive AttackIEEE International Conference on Computer Vision (ICCV), 2019
Aditya Ganeshan
S. VivekB.
R. Venkatesh Babu
AAML
276
131
0
10 Sep 2019
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