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On Adaptive Attacks to Adversarial Example Defenses

On Adaptive Attacks to Adversarial Example Defenses

19 February 2020
Florian Tramèr
Nicholas Carlini
Wieland Brendel
A. Madry
    AAML
ArXivPDFHTML

Papers citing "On Adaptive Attacks to Adversarial Example Defenses"

50 / 540 papers shown
Title
Towards Good Practices in Evaluating Transfer Adversarial Attacks
Towards Good Practices in Evaluating Transfer Adversarial Attacks
Zhengyu Zhao
Hanwei Zhang
Renjue Li
R. Sicre
Laurent Amsaleg
Michael Backes
AAML
4
20
0
17 Nov 2022
MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing
  Attack
MORA: Improving Ensemble Robustness Evaluation with Model-Reweighing Attack
Yunrui Yu
Xitong Gao
Chengzhong Xu
AAML
20
8
0
15 Nov 2022
Physics-Constrained Backdoor Attacks on Power System Fault Localization
Physics-Constrained Backdoor Attacks on Power System Fault Localization
Jianing Bai
Ren Wang
Zuyi Li
AAML
AI4CE
11
5
0
07 Nov 2022
Private and Reliable Neural Network Inference
Private and Reliable Neural Network Inference
Nikola Jovanović
Marc Fischer
Samuel Steffen
Martin Vechev
6
14
0
27 Oct 2022
Improving Adversarial Robustness via Joint Classification and Multiple
  Explicit Detection Classes
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection Classes
Sina Baharlouei
Fatemeh Sheikholeslami
Meisam Razaviyayn
Zico Kolter
AAML
11
5
0
26 Oct 2022
Accelerating Certified Robustness Training via Knowledge Transfer
Accelerating Certified Robustness Training via Knowledge Transfer
Pratik Vaishnavi
Kevin Eykholt
Amir Rahmati
8
7
0
25 Oct 2022
Ares: A System-Oriented Wargame Framework for Adversarial ML
Ares: A System-Oriented Wargame Framework for Adversarial ML
Farhan Ahmed
Pratik Vaishnavi
Kevin Eykholt
Amir Rahmati
AAML
10
7
0
24 Oct 2022
Exploring The Landscape of Distributional Robustness for Question
  Answering Models
Exploring The Landscape of Distributional Robustness for Question Answering Models
Anas Awadalla
Mitchell Wortsman
Gabriel Ilharco
Sewon Min
Ian H. Magnusson
Hannaneh Hajishirzi
Ludwig Schmidt
ELM
OOD
KELM
70
19
0
22 Oct 2022
Hindering Adversarial Attacks with Implicit Neural Representations
Hindering Adversarial Attacks with Implicit Neural Representations
Andrei A. Rusu
D. A. Calian
Sven Gowal
R. Hadsell
AAML
125
4
0
22 Oct 2022
Certified Training: Small Boxes are All You Need
Certified Training: Small Boxes are All You Need
Mark Niklas Muller
Franziska Eckert
Marc Fischer
Martin Vechev
AAML
18
45
0
10 Oct 2022
Symmetry Defense Against CNN Adversarial Perturbation Attacks
Symmetry Defense Against CNN Adversarial Perturbation Attacks
Blerta Lindqvist
AAML
25
2
0
08 Oct 2022
Preprocessors Matter! Realistic Decision-Based Attacks on Machine
  Learning Systems
Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems
Chawin Sitawarin
Florian Tramèr
Nicholas Carlini
AAML
70
8
0
07 Oct 2022
Robustness Certification of Visual Perception Models via Camera Motion
  Smoothing
Robustness Certification of Visual Perception Models via Camera Motion Smoothing
Hanjiang Hu
Zuxin Liu
Linyi Li
Jiacheng Zhu
Ding Zhao
AAML
19
6
0
04 Oct 2022
Stability Analysis and Generalization Bounds of Adversarial Training
Stability Analysis and Generalization Bounds of Adversarial Training
Jiancong Xiao
Yanbo Fan
Ruoyu Sun
Jue Wang
Zhimin Luo
AAML
13
30
0
03 Oct 2022
Adaptive Smoothness-weighted Adversarial Training for Multiple
  Perturbations with Its Stability Analysis
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis
Jiancong Xiao
Zeyu Qin
Yanbo Fan
Baoyuan Wu
Jue Wang
Zhimin Luo
AAML
20
7
0
02 Oct 2022
Understanding Adversarial Robustness Against On-manifold Adversarial
  Examples
Understanding Adversarial Robustness Against On-manifold Adversarial Examples
Jiancong Xiao
Liusha Yang
Yanbo Fan
Jue Wang
Zhimin Luo
OOD
6
13
0
02 Oct 2022
Learning Robust Kernel Ensembles with Kernel Average Pooling
Learning Robust Kernel Ensembles with Kernel Average Pooling
P. Bashivan
Adam Ibrahim
Amirozhan Dehghani
Yifei Ren
OOD
16
5
0
30 Sep 2022
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural
  Networks
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks
Kevin Hector
Mathieu Dumont
Pierre-Alain Moëllic
J. Dutertre
AAML
14
4
0
28 Sep 2022
Audit and Improve Robustness of Private Neural Networks on Encrypted
  Data
Audit and Improve Robustness of Private Neural Networks on Encrypted Data
Jiaqi Xue
Lei Xu
Lin Chen
W. Shi
Kaidi Xu
Qian Lou
AAML
20
5
0
20 Sep 2022
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples
  on Self-Supervised Speech Recognition models
Watch What You Pretrain For: Targeted, Transferable Adversarial Examples on Self-Supervised Speech Recognition models
R. Olivier
H. Abdullah
Bhiksha Raj
AAML
19
1
0
17 Sep 2022
PointCAT: Contrastive Adversarial Training for Robust Point Cloud
  Recognition
PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition
Qidong Huang
Xiaoyi Dong
Dongdong Chen
Hang Zhou
Weiming Zhang
Kui Zhang
Gang Hua
Nenghai Yu
3DPC
17
12
0
16 Sep 2022
Attacking the Spike: On the Transferability and Security of Spiking
  Neural Networks to Adversarial Examples
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples
Nuo Xu
Kaleel Mahmood
Haowen Fang
Ethan Rathbun
Caiwen Ding
Wujie Wen
AAML
27
12
0
07 Sep 2022
Evaluating the Susceptibility of Pre-Trained Language Models via
  Handcrafted Adversarial Examples
Evaluating the Susceptibility of Pre-Trained Language Models via Handcrafted Adversarial Examples
Hezekiah J. Branch
Jonathan Rodriguez Cefalu
Jeremy McHugh
Leyla Hujer
Aditya Bahl
Daniel del Castillo Iglesias
Ron Heichman
Ramesh Darwishi
ELM
SILM
AAML
11
48
0
05 Sep 2022
Towards an Awareness of Time Series Anomaly Detection Models'
  Adversarial Vulnerability
Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability
Shahroz Tariq
B. Le
Simon S. Woo
AAML
AI4TS
14
3
0
24 Aug 2022
Transferability Ranking of Adversarial Examples
Transferability Ranking of Adversarial Examples
Mosh Levy
Guy Amit
Yuval Elovici
Yisroel Mirsky
AAML
18
0
0
23 Aug 2022
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based
  Reinforcement Learning
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning
Eugene Bykovets
Yannick Metz
Mennatallah El-Assady
Daniel A. Keim
J. M. Buhmann
AAML
19
0
0
22 Aug 2022
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D
  Point Cloud Recognition
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition
Jiachen Sun
Weili Nie
Zhiding Yu
Z. Morley Mao
Chaowei Xiao
DiffM
26
25
0
21 Aug 2022
Real-Time Robust Video Object Detection System Against Physical-World
  Adversarial Attacks
Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks
Husheng Han
Xingui Hu
Kaidi Xu
Pucheng Dang
Ying Wang
Yongwei Zhao
Zidong Du
Qi Guo
Yanzhi Yang
Tianshi Chen
AAML
22
2
0
19 Aug 2022
On the Privacy Effect of Data Enhancement via the Lens of Memorization
On the Privacy Effect of Data Enhancement via the Lens of Memorization
Xiao-Li Li
Qiongxiu Li
Zhan Hu
Xiaolin Hu
27
13
0
17 Aug 2022
A Multi-objective Memetic Algorithm for Auto Adversarial Attack
  Optimization Design
A Multi-objective Memetic Algorithm for Auto Adversarial Attack Optimization Design
Jialiang Sun
Wen Yao
Tingsong Jiang
Xiaoqian Chen
AAML
12
0
0
15 Aug 2022
Attacking Adversarial Defences by Smoothing the Loss Landscape
Attacking Adversarial Defences by Smoothing the Loss Landscape
Panagiotis Eustratiadis
H. Gouk
Da Li
Timothy M. Hospedales
AAML
14
4
0
01 Aug 2022
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against
  Adversarial Machine Learning
DNNShield: Dynamic Randomized Model Sparsification, A Defense Against Adversarial Machine Learning
Mohammad Hossein Samavatian
Saikat Majumdar
Kristin Barber
R. Teodorescu
AAML
6
2
0
31 Jul 2022
Do Perceptually Aligned Gradients Imply Adversarial Robustness?
Do Perceptually Aligned Gradients Imply Adversarial Robustness?
Roy Ganz
Bahjat Kawar
Michael Elad
AAML
12
8
0
22 Jul 2022
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Threat Model-Agnostic Adversarial Defense using Diffusion Models
Tsachi Blau
Roy Ganz
Bahjat Kawar
Alex M. Bronstein
Michael Elad
AAML
DiffM
16
26
0
17 Jul 2022
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models
Ronghui Mu
Wenjie Ruan
Leandro Soriano Marcolino
Q. Ni
3DPC
17
10
0
15 Jul 2022
Sound Randomized Smoothing in Floating-Point Arithmetics
Sound Randomized Smoothing in Floating-Point Arithmetics
Václav Voráček
Matthias Hein
12
4
0
14 Jul 2022
Provably Adversarially Robust Nearest Prototype Classifiers
Provably Adversarially Robust Nearest Prototype Classifiers
Václav Voráček
Matthias Hein
AAML
15
11
0
14 Jul 2022
Adversarial Robustness Assessment of NeuroEvolution Approaches
Adversarial Robustness Assessment of NeuroEvolution Approaches
Inês Valentim
Nuno Lourenço
Nuno Antunes
AAML
15
1
0
12 Jul 2022
Machine Learning Security in Industry: A Quantitative Survey
Machine Learning Security in Industry: A Quantitative Survey
Kathrin Grosse
L. Bieringer
Tarek R. Besold
Battista Biggio
Katharina Krombholz
27
31
0
11 Jul 2022
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Dynamic Time Warping based Adversarial Framework for Time-Series Domain
Taha Belkhouja
Yan Yan
J. Doppa
AAML
AI4TS
19
25
0
09 Jul 2022
Adversarial Framework with Certified Robustness for Time-Series Domain
  via Statistical Features
Adversarial Framework with Certified Robustness for Time-Series Domain via Statistical Features
Taha Belkhouja
J. Doppa
AAML
AI4TS
15
11
0
09 Jul 2022
Threat Assessment in Machine Learning based Systems
Threat Assessment in Machine Learning based Systems
L. Tidjon
Foutse Khomh
11
16
0
30 Jun 2022
Increasing Confidence in Adversarial Robustness Evaluations
Increasing Confidence in Adversarial Robustness Evaluations
Roland S. Zimmermann
Wieland Brendel
Florian Tramèr
Nicholas Carlini
AAML
36
16
0
28 Jun 2022
Never trust, always verify : a roadmap for Trustworthy AI?
Never trust, always verify : a roadmap for Trustworthy AI?
L. Tidjon
Foutse Khomh
31
15
0
23 Jun 2022
InfoAT: Improving Adversarial Training Using the Information Bottleneck
  Principle
InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle
Mengting Xu
Tao Zhang
Zhongnian Li
Daoqiang Zhang
AAML
32
16
0
23 Jun 2022
On the Limitations of Stochastic Pre-processing Defenses
On the Limitations of Stochastic Pre-processing Defenses
Yue Gao
Ilia Shumailov
Kassem Fawaz
Nicolas Papernot
AAML
SILM
26
29
0
19 Jun 2022
Demystifying the Adversarial Robustness of Random Transformation
  Defenses
Demystifying the Adversarial Robustness of Random Transformation Defenses
Chawin Sitawarin
Zachary Golan-Strieb
David A. Wagner
AAML
6
20
0
18 Jun 2022
Adversarial Robustness is at Odds with Lazy Training
Adversarial Robustness is at Odds with Lazy Training
Yunjuan Wang
Enayat Ullah
Poorya Mianjy
R. Arora
SILM
AAML
19
10
0
18 Jun 2022
I Know What You Trained Last Summer: A Survey on Stealing Machine
  Learning Models and Defences
I Know What You Trained Last Summer: A Survey on Stealing Machine Learning Models and Defences
Daryna Oliynyk
Rudolf Mayer
Andreas Rauber
16
106
0
16 Jun 2022
Double Sampling Randomized Smoothing
Double Sampling Randomized Smoothing
Linyi Li
Jiawei Zhang
Tao Xie
Bo-wen Li
AAML
6
23
0
16 Jun 2022
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