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Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review

17 September 2019
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Jiliang Tang
Anil K. Jain
    AAML
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Papers citing "Adversarial Attacks and Defenses in Images, Graphs and Text: A Review"

50 / 110 papers shown
Title
Improving Robustness by Enhancing Weak Subnets
Improving Robustness by Enhancing Weak Subnets
Yong Guo
David Stutz
Bernt Schiele
AAML
37
15
0
30 Jan 2022
Post-Training Detection of Backdoor Attacks for Two-Class and
  Multi-Attack Scenarios
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios
Zhen Xiang
David J. Miller
G. Kesidis
AAML
39
47
0
20 Jan 2022
Adversarially Robust Classification by Conditional Generative Model
  Inversion
Adversarially Robust Classification by Conditional Generative Model Inversion
Mitra Alirezaei
Tolga Tasdizen
AAML
21
0
0
12 Jan 2022
Model Stealing Attacks Against Inductive Graph Neural Networks
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen
Xinlei He
Yufei Han
Yang Zhang
24
60
0
15 Dec 2021
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns
Peru Bhardwaj
John D. Kelleher
Luca Costabello
Declan O’Sullivan
184
20
0
11 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against
  Adversarial Attacks
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks
Lijia Yu
Xiao-Shan Gao
AAML
21
5
0
08 Nov 2021
Adversarial Attacks on Knowledge Graph Embeddings via Instance
  Attribution Methods
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods
Peru Bhardwaj
John D. Kelleher
Luca Costabello
Declan O’Sullivan
21
19
0
04 Nov 2021
Multi-Glimpse Network: A Robust and Efficient Classification
  Architecture based on Recurrent Downsampled Attention
Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention
S. Tan
Runpei Dong
Kaisheng Ma
22
2
0
03 Nov 2021
Adversarial Attacks and Defenses for Social Network Text Processing
  Applications: Techniques, Challenges and Future Research Directions
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions
I. Alsmadi
Kashif Ahmad
Mahmoud Nazzal
Firoj Alam
Ala I. Al-Fuqaha
Abdallah Khreishah
A. Algosaibi
AAML
37
16
0
26 Oct 2021
Multi-concept adversarial attacks
Multi-concept adversarial attacks
Vibha Belavadi
Yan Zhou
Murat Kantarcioglu
B. Thuraisingham
AAML
35
0
0
19 Oct 2021
TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural
  Networks
TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks
C. Amarnath
Aishwarya H. Balwani
Kwondo Ma
Abhijit Chatterjee
AAML
23
3
0
16 Oct 2021
Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text
  Style Transfer
Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer
Fanchao Qi
Yangyi Chen
Xurui Zhang
Mukai Li
Zhiyuan Liu
Maosong Sun
AAML
SILM
82
175
0
14 Oct 2021
Inference Attacks Against Graph Neural Networks
Inference Attacks Against Graph Neural Networks
Zhikun Zhang
Min Chen
Michael Backes
Yun Shen
Yang Zhang
MIACV
AAML
GNN
33
50
0
06 Oct 2021
Introducing the DOME Activation Functions
Introducing the DOME Activation Functions
Mohamed E. Hussein
Wael AbdAlmageed
30
1
0
30 Sep 2021
Jointly Attacking Graph Neural Network and its Explanations
Jointly Attacking Graph Neural Network and its Explanations
Wenqi Fan
Wei Jin
Xiaorui Liu
Han Xu
Xianfeng Tang
Suhang Wang
Qing Li
Jiliang Tang
Jianping Wang
Charu C. Aggarwal
AAML
42
28
0
07 Aug 2021
Information Stealing in Federated Learning Systems Based on Generative
  Adversarial Networks
Information Stealing in Federated Learning Systems Based on Generative Adversarial Networks
Yuwei Sun
N. Chong
H. Ochiai
FedML
AAML
20
9
0
02 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Ajmal Mian
Navid Kardan
M. Shah
AAML
41
236
0
01 Aug 2021
Imbalanced Adversarial Training with Reweighting
Imbalanced Adversarial Training with Reweighting
Wentao Wang
Han Xu
Xiaorui Liu
Yaxin Li
B. Thuraisingham
Jiliang Tang
37
16
0
28 Jul 2021
Trustworthy AI: A Computational Perspective
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Jiliang Tang
FaML
104
197
0
12 Jul 2021
Robust Counterfactual Explanations on Graph Neural Networks
Robust Counterfactual Explanations on Graph Neural Networks
Mohit Bajaj
Lingyang Chu
Zihui Xue
J. Pei
Lanjun Wang
P. C. Lam
Yong Zhang
OOD
43
96
0
08 Jul 2021
Survey: Leakage and Privacy at Inference Time
Survey: Leakage and Privacy at Inference Time
Marija Jegorova
Chaitanya Kaul
Charlie Mayor
Alison Q. OÑeil
Alexander Weir
Roderick Murray-Smith
Sotirios A. Tsaftaris
PILM
MIACV
28
71
0
04 Jul 2021
Localized Uncertainty Attacks
Localized Uncertainty Attacks
Ousmane Amadou Dia
Theofanis Karaletsos
C. Hazirbas
Cristian Canton Ferrer
I. Kabul
E. Meijer
AAML
24
2
0
17 Jun 2021
Reveal of Vision Transformers Robustness against Adversarial Attacks
Reveal of Vision Transformers Robustness against Adversarial Attacks
Ahmed Aldahdooh
W. Hamidouche
Olivier Déforges
ViT
15
57
0
07 Jun 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure
  DNN Accelerators
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators
David Stutz
Nandhini Chandramoorthy
Matthias Hein
Bernt Schiele
AAML
MQ
24
18
0
16 Apr 2021
Mitigating Adversarial Attack for Compute-in-Memory Accelerator
  Utilizing On-chip Finetune
Mitigating Adversarial Attack for Compute-in-Memory Accelerator Utilizing On-chip Finetune
Shanshi Huang
Hongwu Jiang
Shimeng Yu
AAML
26
3
0
13 Apr 2021
A Backdoor Attack against 3D Point Cloud Classifiers
A Backdoor Attack against 3D Point Cloud Classifiers
Zhen Xiang
David J. Miller
Siheng Chen
Xi Li
G. Kesidis
3DPC
AAML
36
76
0
12 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima
Relating Adversarially Robust Generalization to Flat Minima
David Stutz
Matthias Hein
Bernt Schiele
OOD
41
65
0
09 Apr 2021
The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review
  of Applications, Techniques, Challenges, and Future Research Directions
The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions
Senthil Kumar Jagatheesaperumal
Mohamed Rahouti
Kashif Ahmad
Ala I. Al-Fuqaha
Mohsen Guizani
AI4CE
17
19
0
06 Apr 2021
Towards Understanding Adversarial Robustness of Optical Flow Networks
Towards Understanding Adversarial Robustness of Optical Flow Networks
Simon Schrodi
Tonmoy Saikia
Thomas Brox
AAML
39
15
0
30 Mar 2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing
  toward digital twin revolution
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
Omer San
Adil Rasheed
T. Kvamsdal
48
50
0
26 Mar 2021
Robust Vision-Based Cheat Detection in Competitive Gaming
Robust Vision-Based Cheat Detection in Competitive Gaming
Aditya Jonnalagadda
I. Frosio
Seth Schneider
M. McGuire
Joohwan Kim
AAML
32
15
0
18 Mar 2021
Understanding the Robustness of Skeleton-based Action Recognition under
  Adversarial Attack
Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack
He Wang
Feixiang He
Zhexi Peng
Tianjia Shao
Yong-Liang Yang
Kun Zhou
David C. Hogg
AAML
40
39
0
09 Mar 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic
  Meta-Learning
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
Ren Wang
Kaidi Xu
Sijia Liu
Pin-Yu Chen
Tsui-Wei Weng
Chuang Gan
Meng Wang
AAML
26
47
0
20 Feb 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data
  Injection Attack Detection in Power Grids
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids
Jiangnan Li
Yingyuan Yang
Jinyuan Stella Sun
K. Tomsovic
Hairong Qi
AAML
39
14
0
17 Feb 2021
Detecting Adversarial Examples by Input Transformations, Defense
  Perturbations, and Voting
Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting
F. Nesti
Alessandro Biondi
Giorgio Buttazzo
AAML
15
39
0
27 Jan 2021
Lattice gauge equivariant convolutional neural networks
Lattice gauge equivariant convolutional neural networks
Matteo Favoni
A. Ipp
David I. Müller
Daniel Schuh
20
45
0
23 Dec 2020
Achieving Adversarial Robustness Requires An Active Teacher
Achieving Adversarial Robustness Requires An Active Teacher
Chao Ma
Lexing Ying
27
1
0
14 Dec 2020
A Deep Marginal-Contrastive Defense against Adversarial Attacks on 1D
  Models
A Deep Marginal-Contrastive Defense against Adversarial Attacks on 1D Models
Mohammed Hassanin
Nour Moustafa
M. Tahtali
AAML
24
2
0
08 Dec 2020
Unsupervised Adversarially-Robust Representation Learning on Graphs
Unsupervised Adversarially-Robust Representation Learning on Graphs
Jiarong Xu
Yang Yang
Junru Chen
Chunping Wang
Xin Jiang
Jiangang Lu
Yizhou Sun
SSL
AAML
OOD
38
36
0
04 Dec 2020
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial
  Learning
Mitigating Gender Bias for Neural Dialogue Generation with Adversarial Learning
Haochen Liu
Wentao Wang
Yiqi Wang
Hui Liu
Zitao Liu
Jiliang Tang
24
71
0
28 Sep 2020
Quantifying the Preferential Direction of the Model Gradient in
  Adversarial Training With Projected Gradient Descent
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent
Ricardo Bigolin Lanfredi
Joyce D. Schroeder
Tolga Tasdizen
27
11
0
10 Sep 2020
Adversarial Patch Camouflage against Aerial Detection
Adversarial Patch Camouflage against Aerial Detection
Ajaya Adhikari
R. D. Hollander
I. Tolios
M. V. Bekkum
Anneloes M. Bal
...
Dennis Gross
N. Jansen
Guillermo A. Pérez
Kit Buurman
S. Raaijmakers
AAML
29
43
0
31 Aug 2020
Can Adversarial Weight Perturbations Inject Neural Backdoors?
Can Adversarial Weight Perturbations Inject Neural Backdoors?
Siddhant Garg
Adarsh Kumar
Vibhor Goel
Yingyu Liang
AAML
48
86
0
04 Aug 2020
Adversarial Example Games
Adversarial Example Games
A. Bose
Gauthier Gidel
Hugo Berrard
Andre Cianflone
Pascal Vincent
Simon Lacoste-Julien
William L. Hamilton
AAML
GAN
38
51
0
01 Jul 2020
Differentiable Language Model Adversarial Attacks on Categorical
  Sequence Classifiers
Differentiable Language Model Adversarial Attacks on Categorical Sequence Classifiers
I. Fursov
A. Zaytsev
Nikita Klyuchnikov
A. Kravchenko
E. Burnaev
AAML
SILM
31
5
0
19 Jun 2020
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue
  Models
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models
Haochen Liu
Zhiwei Wang
Tyler Derr
Jiliang Tang
AAML
22
15
0
27 May 2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
Yaxin Li
Wei Jin
Han Xu
Jiliang Tang
AAML
32
131
0
13 May 2020
Adversarial Training against Location-Optimized Adversarial Patches
Adversarial Training against Location-Optimized Adversarial Patches
Sukrut Rao
David Stutz
Bernt Schiele
AAML
19
92
0
05 May 2020
Learning to fool the speaker recognition
Learning to fool the speaker recognition
Jiguo Li
Xinfeng Zhang
Jizheng Xu
Li Zhang
Y. Wang
Siwei Ma
Wen Gao
AAML
30
21
0
07 Apr 2020
Anomalous Example Detection in Deep Learning: A Survey
Anomalous Example Detection in Deep Learning: A Survey
Saikiran Bulusu
B. Kailkhura
Bo-wen Li
P. Varshney
D. Song
AAML
28
47
0
16 Mar 2020
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