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.
Building Algorithms That Can Find Illicit Bitcoin Transactions
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.
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