What is it about?
This paper includes a comparison between several supervised learning methods on Bitcoin blockchain data. Supervised learning is a subset of AI methods used to automatically classify suspicious behaviour in Bitcoin transactions. AI has shown promising results regarding the used dataset.
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Why is it important?
A massive amount of blockchain data is daily generated, thus it is complicated to process such data. Blockchain is a new type of database in which the transactions are publicly available and anonymised. Thus criminals have the option to conceal in the plain sight. For this reason, machine learning is promising approach to spot out illicit behaviour such as thefts, scams, others... which is expected to inherit specific patterns.
Perspectives
This publication reveals the promising machine learning approach in this kind of datasets in which blockchain is still a young technology. An extensive analysis on different supervised learning has been done which illustrates performance of these algorithms using data derived from Bitcoin. This study is a great start as preliminary study for people interested in this technology.
Ismail Alarab
Bournemouth University
Read the Original
This page is a summary of: Comparative Analysis Using Supervised Learning Methods for Anti-Money Laundering in Bitcoin, June 2020, ACM (Association for Computing Machinery),
DOI: 10.1145/3409073.3409078.
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