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1711.08478
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MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples
22 November 2017
Nicholas Carlini
D. Wagner
AAML
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Papers citing
"MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples"
50 / 135 papers shown
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T. Hapuarachchi
Kaiqi Xiong
Jing Lin
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152
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0
03 Dec 2025
Position: Certified Robustness Does Not (Yet) Imply Model Security
Andrew C. Cullen
Paul Montague
S. Erfani
Benjamin I. P. Rubinstein
251
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0
16 Jun 2025
Classification-Denoising Networks
Louis Thiry
Florentin Guth
303
1
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04 Oct 2024
Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future Prospects
IEEE Access (IEEE Access), 2024
Sabrine Ennaji
Fabio De Gaspari
Dorjan Hitaj
Alicia Kbidi
Luigi V. Mancini
AAML
496
14
0
27 Sep 2024
A Comprehensive Survey on the Security of Smart Grid: Challenges, Mitigations, and Future Research Opportunities
Arastoo Zibaeirad
Farnoosh Koleini
Shengping Bi
Tao Hou
Tao Wang
AAML
232
36
0
10 Jul 2024
Optimal Zero-Shot Detector for Multi-Armed Attacks
Federica Granese
Marco Romanelli
Pablo Piantanida
AAML
248
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0
24 Feb 2024
Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting
Romain Ilbert
Thai V. Hoang
Zonghua Zhang
Themis Palpanas
OOD
AAML
386
1
0
16 Nov 2023
Towards Improving Robustness Against Common Corruptions in Object Detectors Using Adversarial Contrastive Learning
Shashank Kotyan
Danilo Vasconcellos Vargas
AAML
207
0
0
14 Nov 2023
Symmetry Defense Against XGBoost Adversarial Perturbation Attacks
Blerta Lindqvist
AAML
156
0
0
10 Aug 2023
A reading survey on adversarial machine learning: Adversarial attacks and their understanding
Shashank Kotyan
AAML
169
10
0
07 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering
Neural Information Processing Systems (NeurIPS), 2023
Anselm Krainovic
Mahdi Soltanolkotabi
Reinhard Heckel
OOD
133
9
0
24 Jul 2023
Computational Asymmetries in Robust Classification
International Conference on Machine Learning (ICML), 2023
Samuele Marro
M. Lombardi
AAML
153
2
0
25 Jun 2023
Revisiting the Trade-off between Accuracy and Robustness via Weight Distribution of Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Xingxing Wei
Shiji Zhao
Bo li
AAML
383
8
0
06 Jun 2023
Individual Fairness in Bayesian Neural Networks
Alice Doherty
Matthew Wicker
Luca Laurenti
A. Patané
240
5
0
21 Apr 2023
Consistent Valid Physically-Realizable Adversarial Attack against Crowd-flow Prediction Models
Hassan Ali
M. A. Butt
F. Filali
Ala I. Al-Fuqaha
Junaid Qadir
AAML
155
2
0
05 Mar 2023
A Minimax Approach Against Multi-Armed Adversarial Attacks Detection
Federica Granese
Marco Romanelli
S. Garg
Pablo Piantanida
AAML
185
0
0
04 Feb 2023
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
VISIGRAPP (VISIGRAPP), 2022
P. Lorenz
Margret Keuper
J. Keuper
AAML
383
7
0
13 Dec 2022
Symmetry Defense Against CNN Adversarial Perturbation Attacks
Information Security Conference (IS), 2022
Blerta Lindqvist
AAML
308
2
0
08 Oct 2022
A Perturbation Resistant Transformation and Classification System for Deep Neural Networks
Nathaniel R. Dean
D. Sarkar
AAML
102
0
0
25 Aug 2022
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models
Conference on Computer and Communications Security (CCS), 2022
Shawn Shan
Wen-Luan Ding
Emily Wenger
Haitao Zheng
Ben Y. Zhao
AAML
215
15
0
21 May 2022
Deep-Attack over the Deep Reinforcement Learning
Knowledge-Based Systems (KBS), 2022
Yang Li
Quanbiao Pan
Xiaoshi Zhong
AAML
141
16
0
02 May 2022
Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons
International Conference on Artificial Neural Networks (ICANN), 2022
Chandresh Pravin
Ivan Martino
Giuseppe Nicosia
Varun Ojha
AAML
142
2
0
31 Jan 2022
Improving Robustness by Enhancing Weak Subnets
European Conference on Computer Vision (ECCV), 2022
Yong Guo
David Stutz
Bernt Schiele
AAML
345
17
0
30 Jan 2022
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
Network and Distributed System Security Symposium (NDSS), 2022
Yijun Yang
Ruiyuan Gao
Yu Li
Qiuxia Lai
Qiang Xu
GAN
AAML
249
25
0
24 Jan 2022
SoK: Anti-Facial Recognition Technology
Emily Wenger
Shawn Shan
Haitao Zheng
Ben Y. Zhao
PICV
198
19
0
08 Dec 2021
Modeling Adversarial Noise for Adversarial Training
Dawei Zhou
Nannan Wang
Bo Han
Tongliang Liu
AAML
229
18
0
21 Sep 2021
Physical Adversarial Attacks on an Aerial Imagery Object Detector
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Andrew Du
Bo Chen
Tat-Jun Chin
Yee Wei Law
Michele Sasdelli
Ramesh Rajasegaran
Dillon Campbell
AAML
305
79
0
26 Aug 2021
Universal 3-Dimensional Perturbations for Black-Box Attacks on Video Recognition Systems
IEEE Symposium on Security and Privacy (IEEE S&P), 2021
Shangyu Xie
Zheng Chen
Yu Kong
Yuan Hong
AAML
227
30
0
09 Jul 2021
Who is Responsible for Adversarial Defense?
Kishor Datta Gupta
D. Dasgupta
AAML
109
2
0
27 Jun 2021
Delving into the pixels of adversarial samples
Blerta Lindqvist
AAML
92
1
0
21 Jun 2021
Attack to Fool and Explain Deep Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Naveed Akhtar
M. Jalwana
Bennamoun
Lin Wang
AAML
218
35
0
20 Jun 2021
Evaluating the Robustness of Trigger Set-Based Watermarks Embedded in Deep Neural Networks
IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2021
Suyoung Lee
Wonho Song
Suman Jana
M. Cha
Sooel Son
AAML
180
17
0
18 Jun 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*
Ningfei Wang*
Chaowei Xiao
Dawei Yang
Jin Fang
Ruigang Yang
Qi Alfred Chen
Mingyan D. Liu
Yue Liu
AAML
226
280
0
17 Jun 2021
Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training
Dawei Zhou
N. Wang
Xinbo Gao
Bo Han
Jun Yu
Xiaoyu Wang
Tongliang Liu
AAML
157
4
0
10 Jun 2021
Towards Defending against Adversarial Examples via Attack-Invariant Features
International Conference on Machine Learning (ICML), 2021
Dawei Zhou
Tongliang Liu
Bo Han
N. Wang
Chunlei Peng
Xinbo Gao
AAML
138
51
0
09 Jun 2021
Adversarial examples attack based on random warm restart mechanism and improved Nesterov momentum
Tian-zhou Li
AAML
102
1
0
10 May 2021
Self-Supervised Adversarial Example Detection by Disentangled Representation
International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021
Zhaoxi Zhang
L. Zhang
Xufei Zheng
Jinyu Tian
Jiantao Zhou
AAML
DRL
213
10
0
08 May 2021
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
Artificial Intelligence Review (AIR), 2021
Ahmed Aldahdooh
W. Hamidouche
Sid Ahmed Fezza
Olivier Déforges
AAML
688
159
0
01 May 2021
Removing Adversarial Noise in Class Activation Feature Space
IEEE International Conference on Computer Vision (ICCV), 2021
Dawei Zhou
N. Wang
Chunlei Peng
Xinbo Gao
Xiaoyu Wang
Jun Yu
Tongliang Liu
AAML
147
35
0
19 Apr 2021
Attack as Defense: Characterizing Adversarial Examples using Robustness
International Symposium on Software Testing and Analysis (ISSTA), 2021
Zhe Zhao
Guangke Chen
Jingyi Wang
Yiwei Yang
Fu Song
Jun Sun
AAML
170
36
0
13 Mar 2021
Revisiting Model's Uncertainty and Confidences for Adversarial Example Detection
Ahmed Aldahdooh
W. Hamidouche
Olivier Déforges
AAML
275
34
0
09 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN
Desheng Wang
Wei-dong Jin
Yunpu Wu
Aamir Khan
GAN
184
10
0
08 Mar 2021
Online Adversarial Attacks
International Conference on Learning Representations (ICLR), 2021
Andjela Mladenovic
A. Bose
Hugo Berard
William L. Hamilton
Damien Scieur
Pascal Vincent
Gauthier Gidel
AAML
235
12
0
02 Mar 2021
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
Sahar Abdelnabi
Mario Fritz
AAML
113
7
0
09 Feb 2021
Target Training Does Adversarial Training Without Adversarial Samples
Blerta Lindqvist
AAML
144
0
0
09 Feb 2021
Increasing the Confidence of Deep Neural Networks by Coverage Analysis
IEEE Transactions on Software Engineering (TSE), 2021
Giulio Rossolini
Alessandro Biondi
Giorgio Buttazzo
AAML
283
21
0
28 Jan 2021
Defence against adversarial attacks using classical and quantum-enhanced Boltzmann machines
Aidan Kehoe
P. Wittek
Yanbo Xue
Alejandro Pozas-Kerstjens
AAML
278
7
0
21 Dec 2020
Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning
Computers & electrical engineering (CEE), 2020
Ömer Faruk Tuna
Ferhat Ozgur Catak
M. T. Eskil
AAML
283
12
0
11 Dec 2020
FaceGuard: A Self-Supervised Defense Against Adversarial Face Images
IEEE International Conference on Automatic Face & Gesture Recognition (FG), 2020
Debayan Deb
Xiaoming Liu
Anil K. Jain
CVBM
AAML
PICV
237
31
0
28 Nov 2020
Detecting Adversarial Patches with Class Conditional Reconstruction Networks
Perry Deng
Mohammad Saidur Rahman
M. Wright
AAML
197
2
0
11 Nov 2020
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