A Supervised Model to Detect Suspicious Activities in the Bitcoin Network

A Supervised Model to Detect Suspicious Activities in the Bitcoin Network

Shortly after its official launch in 2009, Bitcoin has gained rapid popularity worldwide, which in return attracted a variety of people especially malicious attackers, who get the advantage of its pseudo-anonymity to institute un-traceable threats, scams, and criminal activities. Recently, some Bitc...

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Bibliographic Details
Main Authors: Al-Hashedi K.G., Magalingam P., Maarop N., Samy G.N., Rahim F.B.A., Shanmugam M., Hasan M.K.
Other Authors: 57224367919
Format: Conference Paper
Published: Springer Science and Business Media Deutschland GmbH 2024
Subjects:
Bitcoin
Cybercrime
Fraud detection
Illicit addresses
Machine learning
Balancing
Classification (of information)
Crime
Criminal activities
Cyber-crimes
Fraud detection system
Illicit address
Labeled dataset
Machine-learning
Supervised classifiers
Suspicious behaviours
Verification process
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