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The GANfather: Controllable generation of malicious activity to improve defence systems

The GANfather: Controllable generation of malicious activity to improve defence systems

Ricardo Pereira
Jacopo Bono
João Tiago Ascensão
David Oliveira Aparício
Pedro Ribeiro
P. Bizarro
    AAML
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Papers citing "The GANfather: Controllable generation of malicious activity to improve defence systems"

4 / 4 papers shown
Title
Controllable Data Generation by Deep Learning: A Review
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang
Yuanqi Du
Xiaojie Guo
Bo Pan
Zhaohui Qin
Liang Zhao
58
28
0
19 Jul 2022
Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack
Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack
Fan Wu
Min Gao
Junliang Yu
Zongwei Wang
Kecheng Liu
Wange Xu
AAML
44
35
0
22 Jul 2021
GuiltyWalker: Distance to illicit nodes in the Bitcoin network
GuiltyWalker: Distance to illicit nodes in the Bitcoin network
C. Oliveira
Joao Torres
Maria Inês Silva
David Oliveira Aparício
João Tiago Ascensão
P. Bizarro
28
24
0
10 Feb 2021
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Joana Lorenz
Maria Inês Silva
David Oliveira Aparício
João Tiago Ascensão
P. Bizarro
33
102
0
29 May 2020

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