Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89030
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Martins, Ana P. | por |
dc.contributor.author | Brito, Miguel A. | por |
dc.date.accessioned | 2024-02-23T15:00:33Z | - |
dc.date.issued | 2023-01-01 | - |
dc.identifier.isbn | 9789898704504 | por |
dc.identifier.uri | https://hdl.handle.net/1822/89030 | - |
dc.description.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. | por |
dc.description.sponsorship | FCT -Fundação para a Ciência e a Tecnologia(UIDB/00319/2020) | por |
dc.language.iso | eng | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT | por |
dc.rights | restrictedAccess | por |
dc.subject | AML | por |
dc.subject | Cryptocurrencies | por |
dc.subject | Fraud detection | por |
dc.subject | Graphs | por |
dc.subject | Machine learning | por |
dc.title | Fraud detection and anti-money laundering applying machine learning techniques in cryptocurrency transactional graphs | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
oaire.citationStartPage | 364 | por |
oaire.citationEndPage | 368 | por |
dc.date.updated | 2024-02-10T22:29:37Z | - |
dc.date.embargo | 10000-01-01 | - |
sdum.export.identifier | 13250 | - |
sdum.conferencePublication | Proceedings of the International Conferences on ICT, Society, and Human Beings 2023, ICT 2023; and e-Health 2023, EH 2023; Connected Smart Cities 2023, CSC 2023; and Big Data Analytics, Data Mining and Computational Intelligence 2023, BigDaCI 2023 | por |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Fraud Detection and Anti-Money Laundering Applying Machine Learning Techniques in Cryptocurrency Transactional Graphs.pdf Acesso restrito! | 121,51 kB | Adobe PDF | Ver/Abrir |