Tracing Cryptocurrency Laundering after Ransomware Attack

Cybercriminals are attacking vulnerable systems in all domains and demand ransoms to return their control [2]. This money is paid by anonymous payment systems such as cryptocurrency (e.g., bitcoin) to evade law enforcement [6]. Bitcoin transactions are irrefutable, which guarantees that once the ransom is paid, the money will not be charged back, unlike credit card transactions. Additionally, it allows cybercriminals to cash out large proceeds of their criminal activities (tens of millions of dollars). Tracking ransomware payments is near to impossible due to complicated bitcoin movements within blockchain [4]. We will examine existing machine learning techniques to identify the limitations behind tracing such fraudulent transactions, and the flow of ransom cryptocurrency, common patterns associated with these fraudulent activities and other ransomware actors involved. Eventually, financial firms will be able to recover bitcoins paid after ransomware attacks and will have the opportunity to detect such flows earlier, protecting their customers.

Faculty Supervisor:

Jonathan Anderson

Student:

Partner:

NASDAQ Canada Inc

Discipline:

Computer science

Sector:

Finance and Insurance; Health and Related Sciences & Technology; Information and Communications Technology

University:

Memorial University of Newfoundland

Program: