Home BlogDataset Building Algorithms That Can Find Illicit Bitcoin Transactions

Building Algorithms That Can Find Illicit Bitcoin Transactions

by Michael McLaughlin
by

Elliptic, a blockchain analytics firm, MIT, and IBM have released a dataset of 200,000 bitcoin transactions to foster the development of machine learning algorithms that can detect illicit transactions. The groups labeled the transactions, which total $6 billion, as licit, illicit and unknown. Each transaction also has an associated 166 features, such as the transaction fee and a time interval for when a transaction appeared on the blockchain. 

Get the data.

Image: Pixabay

1
FacebookTwitterPinterestEmail
Avatar photo
Michael McLaughlin

Michael McLaughlin is a research analyst at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.

You may also like

Detecting Neurodegenerative Diseases in Slovak Speakers

Enhancing Energy Efficiency on University Campuses

Advancing Precision Medicine Techniques

Enabling Biometric Recognition

Examining Grassland Grazing Intensity in Mainland China

Understanding Societal Progress

Compiling Agricultural Experiments Data

Training Activity Recognition Models

Identifying Hand Movements

Creating Digital Twins

Show Buttons
Hide Buttons