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Detecting Adversarial Examples by Input Transformations, Defense
  Perturbations, and Voting
v1v2 (latest)

Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting

27 January 2021
F. Nesti
Alessandro Biondi
Giorgio Buttazzo
    AAML
ArXiv (abs)PDFHTML

Papers citing "Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting"

14 / 14 papers shown
Title
Detection of Adversarial Physical Attacks in Time-Series Image Data
Detection of Adversarial Physical Attacks in Time-Series Image Data
Ramneet Kaur
Y. Kantaros
Wenwen Si
James Weimer
Insup Lee
AAML
46
3
0
27 Apr 2023
Targeted Adversarial Attacks against Neural Network Trajectory
  Predictors
Targeted Adversarial Attacks against Neural Network Trajectory Predictors
Kai Liang Tan
Jun Wang
Y. Kantaros
AAML
82
15
0
08 Dec 2022
Defending From Physically-Realizable Adversarial Attacks Through
  Internal Over-Activation Analysis
Defending From Physically-Realizable Adversarial Attacks Through Internal Over-Activation Analysis
Giulio Rossolini
F. Nesti
Fabio Brau
Alessandro Biondi
Giorgio Buttazzo
AAML
61
10
0
14 Mar 2022
Boundary Defense Against Black-box Adversarial Attacks
Boundary Defense Against Black-box Adversarial Attacks
Manjushree B. Aithal
Xiaohua Li
AAML
76
6
0
31 Jan 2022
On the Real-World Adversarial Robustness of Real-Time Semantic
  Segmentation Models for Autonomous Driving
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving
Giulio Rossolini
F. Nesti
G. D’Amico
Saasha Nair
Alessandro Biondi
Giorgio Buttazzo
AAML
83
41
0
05 Jan 2022
On the Minimal Adversarial Perturbation for Deep Neural Networks with
  Provable Estimation Error
On the Minimal Adversarial Perturbation for Deep Neural Networks with Provable Estimation Error
Fabio Brau
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
63
8
0
04 Jan 2022
Towards Understanding and Harnessing the Effect of Image Transformation
  in Adversarial Detection
Towards Understanding and Harnessing the Effect of Image Transformation in Adversarial Detection
Hui Liu
Bo Zhao
Yuefeng Peng
Weidong Li
Peng Liu
AAML
68
1
0
04 Jan 2022
Simple Post-Training Robustness Using Test Time Augmentations and Random
  Forest
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest
Gilad Cohen
Raja Giryes
AAML
71
4
0
16 Sep 2021
Evaluating the Robustness of Semantic Segmentation for Autonomous
  Driving against Real-World Adversarial Patch Attacks
Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks
F. Nesti
Giulio Rossolini
Saasha Nair
Alessandro Biondi
Giorgio Buttazzo
AAML
86
76
0
13 Aug 2021
Unsupervised Detection of Adversarial Examples with Model Explanations
Unsupervised Detection of Adversarial Examples with Model Explanations
Gihyuk Ko
Gyumin Lim
AAMLGAN
41
5
0
22 Jul 2021
Anomaly Detection of Adversarial Examples using Class-conditional
  Generative Adversarial Networks
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial Networks
Hang Wang
David J. Miller
G. Kesidis
GANAAML
50
13
0
21 May 2021
Adversarial Examples Detection with Bayesian Neural Network
Adversarial Examples Detection with Bayesian Neural Network
Yao Li
Tongyi Tang
Cho-Jui Hsieh
T. C. Lee
GANAAML
60
3
0
18 May 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis
Increasing the Confidence of Deep Neural Networks by Coverage Analysis
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
71
15
0
28 Jan 2021
Defending Adversarial Attacks via Semantic Feature Manipulation
Defending Adversarial Attacks via Semantic Feature Manipulation
Shuo Wang
Tianle Chen
Surya Nepal
Carsten Rudolph
M. Grobler
Shangyu Chen
AAML
51
7
0
03 Feb 2020
1