How to Not Get Caught When You Launder Money on Blockchain?
arXiv:2010.15082
Abstract
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.
References in corpus (5)
- Bitcoin Transaction Graph Analysis
- On the Economic Significance of Ransomware Campaigns: A Bitcoin Transactions Perspective
- Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
- Tracing Transactions Across Cryptocurrency Ledgers
- Obfuscation in Bitcoin: Techniques and Politics