|
Title:
|
FRAUD DETECTION AND ANTI-MONEY LAUNDERING APPLYING MACHINE LEARNING TECHNIQUES IN CRYPTOCURRENCY TRANSACTIONAL GRAPHS |
|
Author(s):
|
Ana P. Martins and Miguel A. Brito |
|
ISBN:
|
978-989-8704-50-4 |
|
Editors:
|
Piet Kommers, Mário Macedo, Guo Chao Peng and Ajith Abraham |
|
Year:
|
2023 |
|
Edition:
|
Single |
|
Keywords:
|
AML, Cryptocurrencies, Graphs, Machine Learning, Fraud Detection |
|
Type:
|
Short |
|
First Page:
|
364 |
|
Last Page:
|
368 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Cryptocurrencies have advantages such as lower costs, efficiency, and security, but are vulnerable to fraud due to a lack of controls and anonymity. Criminals use virtual currencies for quick, anonymous transactions. Robust measures are needed to prevent illegal activities like money laundering. Machine learning (ML) and graph analysis can help detect fraud in the cryptocurrency market, despite criminals mimicking normal transactions. This study aims to use cutting-edge technologies like ML and graph learning to find fraudulent patterns in cryptocurrency transactions. |
|
|
|
|
|
|
