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Adversarial Attacks on Deep Models for Financial Transaction Records

Adversarial Attacks on Deep Models for Financial Transaction Records

15 June 2021
I. Fursov
Matvey Morozov
N. Kaploukhaya
Elizaveta Kovtun
Rodrigo Rivera-Castro
Gleb Gusev
Dmitrii Babaev
Ivan Kireev
Alexey Zaytsev
Evgeny Burnaev
    AAML
ArXiv (abs)PDFHTML

Papers citing "Adversarial Attacks on Deep Models for Financial Transaction Records"

24 / 24 papers shown
Title
No Query, No Access
No Query, No Access
Wenjie Wang
Siyuan Liang
Yize Zhang
Xiaojun Jia
Hao Lin
Xiaochun Cao
AAML
96
1
0
12 May 2025
Diffusion Transformers for Tabular Data Time Series Generation
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti
E. Sangineto
Simone Luetto
L. Forni
Rita Cucchiara
216
0
0
10 Apr 2025
Assessing Robustness via Score-Based Adversarial Image Generation
Assessing Robustness via Score-Based Adversarial Image Generation
Marcel Kollovieh
Lukas Gosch
Yan Scholten
Marten Lienen
Leo Schwinn
Stephan Günnemann
DiffM
111
6
0
06 Oct 2023
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
Evgeny Burnaev
AAMLSILM
43
5
0
19 Jun 2020
Gradient-based adversarial attacks on categorical sequence models via
  traversing an embedded world
Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world
I. Fursov
Alexey Zaytsev
Nikita Klyuchnikov
A. Kravchenko
Evgeny Burnaev
AAMLSILM
46
11
0
09 Mar 2020
E.T.-RNN: Applying Deep Learning to Credit Loan Applications
E.T.-RNN: Applying Deep Learning to Credit Loan Applications
Dmitrii Babaev
M. Savchenko
Alexander Tuzhilin
Dmitrii Umerenkov
55
88
0
06 Nov 2019
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
Han Xu
Yao Ma
Haochen Liu
Debayan Deb
Hui Liu
Jiliang Tang
Anil K. Jain
AAML
79
678
0
17 Sep 2019
BERTScore: Evaluating Text Generation with BERT
BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang
Varsha Kishore
Felix Wu
Kilian Q. Weinberger
Yoav Artzi
360
5,872
0
21 Apr 2019
Adversarial Attack and Defense on Graph Data: A Survey
Adversarial Attack and Defense on Graph Data: A Survey
Lichao Sun
Yingtong Dou
Carl Yang
Ji Wang
Yixin Liu
Philip S. Yu
Lifang He
Yangqiu Song
GNNAAML
94
284
0
26 Dec 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,229
0
11 Oct 2018
Adversarial Attacks and Defences: A Survey
Adversarial Attacks and Defences: A Survey
Anirban Chakraborty
Manaar Alam
Vishal Dey
Anupam Chattopadhyay
Debdeep Mukhopadhyay
AAMLOOD
89
683
0
28 Sep 2018
Black-box Generation of Adversarial Text Sequences to Evade Deep
  Learning Classifiers
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Ji Gao
Jack Lanchantin
M. Soffa
Yanjun Qi
AAML
142
725
0
13 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A
  Survey
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Ajmal Mian
AAML
99
1,870
0
02 Jan 2018
Adversarial Examples: Attacks and Defenses for Deep Learning
Adversarial Examples: Attacks and Defenses for Deep Learning
Xiaoyong Yuan
Pan He
Qile Zhu
Xiaolin Li
SILMAAML
101
1,625
0
19 Dec 2017
Art of singular vectors and universal adversarial perturbations
Art of singular vectors and universal adversarial perturbations
Valentin Khrulkov
Ivan Oseledets
AAML
64
132
0
11 Sep 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILMOOD
319
12,151
0
19 Jun 2017
Deep Text Classification Can be Fooled
Deep Text Classification Can be Fooled
Bin Liang
Hongcheng Li
Miaoqiang Su
Pan Bian
Xirong Li
Wenchang Shi
AAML
75
426
0
26 Apr 2017
Detecting Adversarial Samples from Artifacts
Detecting Adversarial Samples from Artifacts
Reuben Feinman
Ryan R. Curtin
S. Shintre
Andrew B. Gardner
AAML
105
894
0
01 Mar 2017
On Detecting Adversarial Perturbations
On Detecting Adversarial Perturbations
J. H. Metzen
Tim Genewein
Volker Fischer
Bastian Bischoff
AAML
75
950
0
14 Feb 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILMAAML
547
5,912
0
08 Jul 2016
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Crafting Adversarial Input Sequences for Recurrent Neural Networks
Nicolas Papernot
Patrick McDaniel
A. Swami
Richard E. Harang
AAMLGANSILM
61
456
0
28 Apr 2016
Learning with a Strong Adversary
Learning with a Strong Adversary
Ruitong Huang
Bing Xu
Dale Schuurmans
Csaba Szepesvári
AAML
84
358
0
10 Nov 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
282
19,129
0
20 Dec 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
289
14,968
1
21 Dec 2013
1