How to Not Get Caught When You Launder Money on Blockchain?
The number of blockchain users has tremendously grown in recent years. As an unintended consequence, e-crime transactions on blockchains has been on the rise. Consequently, public blockchains have become a hotbed of research for developing AI tools to detect and trace users and transactions that are related to e-crime. We argue that following a few select strategies can make money laundering on blockchain virtually undetectable with most of the existing tools and algorithms. As a result, the effective combating of e-crime activities involving cryptocurrencies requires the development of novel analytic methodology in AI.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity
Every year, criminals launder billions of dollars acquired from serious felonies (e.g., terrorism, drug smuggling, or human trafficking) harming countless people and economies. Cryptocurrencies, in particular, have devel…
Active LearningAnomaly DetectionUnsupervised Anomaly DetectionIdentifying Money Laundering Subgraphs on the Blockchain
Anti-Money Laundering (AML) involves the identification of money laundering crimes in financial activities, such as cryptocurrency transactions. Recent studies advanced AML through the lens of graph-based machine learnin…
BenchmarkingThe Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset
Subgraph representation learning is a technique for analyzing local structures (or shapes) within complex networks. Enabled by recent developments in scalable Graph Neural Networks (GNNs), this approach encodes relationa…
Representation LearningFinding Money Launderers Using Heterogeneous Graph Neural Networks
Current anti-money laundering (AML) systems, predominantly rule-based, exhibit notable shortcomings in efficiently and precisely detecting instances of money laundering. As a result, there has been a recent surge toward …
Graph Neural NetworkEthereum transaction tracking: Inferring evolution of transaction networks via link prediction
Blockchain is an emerging technology which has attracted wide attention in recent years. As one of the blockchain applications, cryptocurrency has developed rapidly in recent years, attracting criminals to commit fraud a…