A Supervised Model to Detect Suspicious Activities in the Bitcoin Network

• 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

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...