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...
Saved in:
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: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fraud detection by machine learning techniques
by: Khai, Wah Khaw, et al.
Published: (2023) -
Fraud detection in shipping industry based on location using machine learning comparison techniques
by: Ganesan Subramaniam, Mr.
Published: (2023) -
Contributing factors of fraud intention behavior: a case of Royal Malaysian Police in Kelantan / NIk Zati Afiqah Sapiaa @ Md Nordin
by: Sapiaa @ Md Nordin, NIk Zati Afiqah
Published: (2021) -
Cyberbully Detection Survey: Malay-English Glossary of Cyberbullying Incidents
by: Din M.M., et al.
Published: (2024) -
The determinants of fraud prevention effectiveness in Malaysian local authorities: the mediating roles of levers of control / Razif Rosli
by: Rosli, Razif
Published: (2022)