Description

Money Laundering is a kind of financial crime that converts proceeds of crime and further disguises the illicit origin of money brought in the economic system of a State. The scope of money laundering is extensive especially conceived as in recent times by taking into account the emerging challenges arising from digital technologies being used in deriving the illegal sources of money and integrating it back to the financial resources of the states. Virtual currency in online social networks (OSN) plays an increasingly important role in supporting various financial activities like currency exchange, online shopping, and paid games. Users usually purchase virtual currency using real currency. This fact motivates attackers to instrument a military of accounts to gather virtual currency unethically or illegally with no or very low cost then launder the collected virtual money for massive profit. Such attacks not only introduce significant loss of victim users, but also harm the viability of the ecosystem. The system is developed the machine learning algorithm for detecting the money laundering account effectively. The system is also developed the machine learning algorithm such as Gradient Boosting Algorithm and Random Forest. The experimental results shows that accuracy, precision, recall, f1-score.