Classification, affiliation, and deanonymization of cryptocurrency activities

Bloomberg recently reported that theft and embezzlement of cryptocurrencies, such as Bitcoin and Ether, have become an annual USD $200 million business. Indeed, just between January 2021 and March 2022 investors have lost over US$1 billion in cryptocurrency scams according to the report by the US’s Federal Trade Commission. More than 46,000 people have lost money in crypto fraud since the beginning of 2021, making it the leading source of payment scams. Cryptocurrency has become a vehicle for money laundering, payments for ransomware, illicit activity, and even funding of extremist groups. As the use of crypto technology continues to proliferate, the losses are projected to increase to even larger amounts. Understanding who is a recipient (e.g., initiators of ransomware) or sender (e.g., supporters of extremists) of these funds is critical. For example, tracing the source of extremists’ facilitators can help enforce accountability, assist in mitigating and controlling the extent of their influence, and most importantly deter future similar activities. Our research aims to enable efficient and accurate blockchain accounts’ tracking, analysis, affiliation, and de-anonymization of participating entities. This project will focus on bringing our innovative research idea to market.

Faculty Supervisor:

Natalia Stakhanova

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Computer science

Sector:

Cyber Security; Information and Communications Technology; Technology

University:

University of Saskatchewan

Program: