Anti-money Laundering Analytics on the Bitcoin Transactions

会议论文
发表日期：

2024年

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Rajendra Hegadi,
Bhavya Tripathi,
S. Namratha,
Aqtar Parveez,
Animesh Chaturvedi,
M. Hariprasad,
P. Priyanga

摘要

Bitcoin is a popular cryptocurrency widely used for cross-border transactions. Anonymity, immutability, and decentralization are the major features of Bitcoin. However, criminals have taken advantage of these very features, resulting in the rise of illegal and fraudulent activities using the innovative technology of blockchain. This paper investigates the behavioral patterns of illicit transactions in the Bitcoin dataset and applies Machine Learning (ML) techniques to see how well they detect these transactions. The aim is to provide an insight into how ML techniques can support the proposed Anti-Money Laundering Analytics on the Bitcoin Transactions. The motivation behind this work stems from the recent COVID-19 pandemic, which saw a significant spike in various cybercrimes, particularly cybercrimes involving cryptocurrencies.