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On Detecting Adversarial Perturbations

On Detecting Adversarial Perturbations

14 February 2017
J. H. Metzen
Tim Genewein
Volker Fischer
Bastian Bischoff
    AAML
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Papers citing "On Detecting Adversarial Perturbations"

50 / 187 papers shown
Title
Active Light Modulation to Counter Manipulation of Speech Visual Content
Active Light Modulation to Counter Manipulation of Speech Visual Content
Hadleigh Schwartz
Xiaofeng Yan
Charles J. Carver
Xia Zhou
73
0
0
30 Apr 2025
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident
  Failing Samples for Deep Learning Models
A3Rank: Augmentation Alignment Analysis for Prioritizing Overconfident Failing Samples for Deep Learning Models
Zhengyuan Wei
Haipeng Wang
Qili Zhou
William Chan
34
0
0
19 Jul 2024
Understanding Deep Learning defenses Against Adversarial Examples
  Through Visualizations for Dynamic Risk Assessment
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment
Xabier Echeberria-Barrio
Amaia Gil-Lerchundi
Jon Egana-Zubia
Raul Orduna Urrutia
AAML
37
6
0
12 Feb 2024
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds
Hejia Geng
Peng Li
AAML
42
3
0
20 Aug 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty
  Estimation for Adversarial Robustness
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness
Ruoxi Qin
Linyuan Wang
Xuehui Du
Xing-yuan Chen
Binghai Yan
AAML
34
0
0
01 Aug 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
Noise robust neural network architecture
Noise robust neural network architecture
Yunuo Xiong
Hongwei Xiong
27
1
0
16 May 2023
Simultaneous Adversarial Attacks On Multiple Face Recognition System
  Components
Simultaneous Adversarial Attacks On Multiple Face Recognition System Components
Inderjeet Singh
Kazuya Kakizaki
Toshinori Araki
CVBM
AAML
PICV
29
0
0
11 Apr 2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
Yuguang Yao
Jiancheng Liu
Yifan Gong
Xiaoming Liu
Yanzhi Wang
X. Lin
Sijia Liu
AAML
MLAU
39
1
0
13 Mar 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive
  Smoothing
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing
Yatong Bai
Brendon G. Anderson
Aerin Kim
Somayeh Sojoudi
AAML
41
18
0
29 Jan 2023
Vertex-based reachability analysis for verifying ReLU deep neural
  networks
Vertex-based reachability analysis for verifying ReLU deep neural networks
João G. Zago
E. Camponogara
Eric A. Antonelo
AAML
31
2
0
27 Jan 2023
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion
  Attacks against Network Intrusion Detection Systems
TAD: Transfer Learning-based Multi-Adversarial Detection of Evasion Attacks against Network Intrusion Detection Systems
Islam Debicha
Richard Bauwens
Thibault Debatty
Jean-Michel Dricot
Tayeb Kenaza
Wim Mees
AAML
24
40
0
27 Oct 2022
Improving Adversarial Robustness with Self-Paced Hard-Class Pair
  Reweighting
Improving Adversarial Robustness with Self-Paced Hard-Class Pair Reweighting
Peng-Fei Hou
Jie Han
Xingyu Li
AAML
OOD
23
11
0
26 Oct 2022
Universal Evasion Attacks on Summarization Scoring
Universal Evasion Attacks on Summarization Scoring
Wenchuan Mu
Kwan Hui Lim
AAML
43
1
0
25 Oct 2022
Visual Prompting for Adversarial Robustness
Visual Prompting for Adversarial Robustness
Aochuan Chen
P. Lorenz
Yuguang Yao
Pin-Yu Chen
Sijia Liu
VLM
VPVLM
40
32
0
12 Oct 2022
Robust Models are less Over-Confident
Robust Models are less Over-Confident
Julia Grabinski
Paul Gavrikov
J. Keuper
M. Keuper
AAML
36
24
0
12 Oct 2022
Constraining Representations Yields Models That Know What They Don't
  Know
Constraining Representations Yields Models That Know What They Don't Know
João Monteiro
Pau Rodríguez López
Pierre-Andre Noel
I. Laradji
David Vazquez
AAML
44
0
0
30 Aug 2022
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps
Mohammadreza Amirian
Friedhelm Schwenker
Thilo Stadelmann
AAML
27
16
0
24 Aug 2022
Design of secure and robust cognitive system for malware detection
Design of secure and robust cognitive system for malware detection
Sanket Shukla
AAML
27
2
0
03 Aug 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
41
16
0
28 Jun 2022
Attack-Agnostic Adversarial Detection
Attack-Agnostic Adversarial Detection
Jiaxin Cheng
Mohamed Hussein
J. Billa
Wael AbdAlmageed
AAML
28
0
0
01 Jun 2022
Semantic interpretation for convolutional neural networks: What makes a
  cat a cat?
Semantic interpretation for convolutional neural networks: What makes a cat a cat?
Haonan Xu
Yuntian Chen
Dongxiao Zhang
FAtt
33
3
0
16 Apr 2022
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization
  Perspective
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Yimeng Zhang
Yuguang Yao
Jinghan Jia
Jinfeng Yi
Min-Fong Hong
Shiyu Chang
Sijia Liu
AAML
28
33
0
27 Mar 2022
A Survey of Robust Adversarial Training in Pattern Recognition:
  Fundamental, Theory, and Methodologies
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies
Zhuang Qian
Kaizhu Huang
Qiufeng Wang
Xu-Yao Zhang
OOD
AAML
ObjD
54
72
0
26 Mar 2022
Detection of Word Adversarial Examples in Text Classification: Benchmark
  and Baseline via Robust Density Estimation
Detection of Word Adversarial Examples in Text Classification: Benchmark and Baseline via Robust Density Estimation
Kiyoon Yoo
Jangho Kim
Jiho Jang
Nojun Kwak
24
39
0
03 Mar 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
25
11
0
21 Feb 2022
White-Box Attacks on Hate-speech BERT Classifiers in German with
  Explicit and Implicit Character Level Defense
White-Box Attacks on Hate-speech BERT Classifiers in German with Explicit and Implicit Character Level Defense
Shahrukh Khan
Mahnoor Shahid
Navdeeppal Singh
AAML
39
3
0
11 Feb 2022
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving
  Scenarios
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios
Jung Im Choi
Qing Tian
AAML
30
38
0
10 Feb 2022
Adversarial Detector with Robust Classifier
Adversarial Detector with Robust Classifier
Takayuki Osakabe
Maungmaung Aprilpyone
Sayaka Shiota
Hitoshi Kiya
AAML
21
1
0
05 Feb 2022
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial
  Examples Against Traffic Sign Recognition Systems
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems
Wei Jia
Zhaojun Lu
Haichun Zhang
Zhenglin Liu
Jie Wang
Gang Qu
AAML
16
51
0
17 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
42
7
0
04 Jan 2022
DeepAdversaries: Examining the Robustness of Deep Learning Models for
  Galaxy Morphology Classification
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification
A. Ćiprijanović
Diana Kafkes
Gregory F. Snyder
F. Sánchez
G. Perdue
K. Pedro
Brian D. Nord
Sandeep Madireddy
Stefan M. Wild
AAML
42
15
0
28 Dec 2021
Constrained Gradient Descent: A Powerful and Principled Evasion Attack
  Against Neural Networks
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks
Weiran Lin
Keane Lucas
Lujo Bauer
Michael K. Reiter
Mahmood Sharif
AAML
31
5
0
28 Dec 2021
Data Collection and Quality Challenges in Deep Learning: A Data-Centric
  AI Perspective
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective
Steven Euijong Whang
Yuji Roh
Hwanjun Song
Jae-Gil Lee
27
326
0
13 Dec 2021
Medical Aegis: Robust adversarial protectors for medical images
Medical Aegis: Robust adversarial protectors for medical images
Qingsong Yao
Zecheng He
S. Kevin Zhou
AAML
MedIm
30
2
0
22 Nov 2021
Detecting AutoAttack Perturbations in the Frequency Domain
Detecting AutoAttack Perturbations in the Frequency Domain
P. Lorenz
P. Harder
Dominik Strassel
M. Keuper
J. Keuper
AAML
19
13
0
16 Nov 2021
Robust and Accurate Object Detection via Self-Knowledge Distillation
Robust and Accurate Object Detection via Self-Knowledge Distillation
Weipeng Xu
Pengzhi Chu
Renhao Xie
Xiongziyan Xiao
Hongcheng Huang
AAML
ObjD
27
4
0
14 Nov 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
Yonggan Fu
Qixuan Yu
Yang Zhang
Shan-Hung Wu
Ouyang Xu
David D. Cox
Yingyan Lin
AAML
OOD
33
29
0
26 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
Fast Gradient Non-sign Methods
Fast Gradient Non-sign Methods
Yaya Cheng
Jingkuan Song
Xiaosu Zhu
Qilong Zhang
Lianli Gao
Heng Tao Shen
AAML
29
11
0
25 Oct 2021
Trustworthy AI: From Principles to Practices
Trustworthy AI: From Principles to Practices
Bo-wen Li
Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
119
357
0
04 Oct 2021
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
Neil G. Marchant
Benjamin I. P. Rubinstein
Scott Alfeld
MU
AAML
28
69
0
17 Sep 2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks
TREATED:Towards Universal Defense against Textual Adversarial Attacks
Bin Zhu
Zhaoquan Gu
Le Wang
Zhihong Tian
AAML
36
8
0
13 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
Yonggan Fu
Yang Katie Zhao
Qixuan Yu
Chaojian Li
Yingyan Lin
AAML
52
12
0
11 Sep 2021
Benchmarking the Robustness of Instance Segmentation Models
Benchmarking the Robustness of Instance Segmentation Models
Said Fahri Altindis
Yusuf Dalva
Hamza Pehlivan
Aysegül Dündar
VLM
OOD
29
12
0
02 Sep 2021
PatchCleanser: Certifiably Robust Defense against Adversarial Patches
  for Any Image Classifier
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image Classifier
Chong Xiang
Saeed Mahloujifar
Prateek Mittal
VLM
AAML
24
73
0
20 Aug 2021
Optical Adversarial Attack
Optical Adversarial Attack
Abhiram Gnanasambandam
A. Sherman
Stanley H. Chan
AAML
35
65
0
13 Aug 2021
AdvRush: Searching for Adversarially Robust Neural Architectures
AdvRush: Searching for Adversarially Robust Neural Architectures
J. Mok
Byunggook Na
Hyeokjun Choe
Sungroh Yoon
OOD
AAML
22
44
0
03 Aug 2021
Unsupervised Detection of Adversarial Examples with Model Explanations
Unsupervised Detection of Adversarial Examples with Model Explanations
Gihyuk Ko
Gyumin Lim
AAML
GAN
39
5
0
22 Jul 2021
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang
Eunjung Lee
Wonjong Rhee
AAML
167
15
0
14 Jul 2021
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