How Algorithms Can Help Track Cryptocurrency Crime

When Sarah Meiklejohn first discovered cryptocurrency, she was a graduate student in computer science at the University of California, San Diego.

“In the beginning we were all just like ‘whoa, Bitcoin what’s anybody doing with it,'” she said.

This was back in 2013, four years after Bitcoin was dreamed up in a white paper by someone called Satoshi Nakamoto, and back then it was generally accepted that Bitcoin was untraceable, which was strange because Bitcoin transactions are public.

They are all represented by a meaningless string of characters – or hashes – on a digital ledger called the blockchain.

Meiklejohn believed that when a cryptocurrency transaction touched the real world, the supposed meaninglessness of these hashes would fall away, and the transactions would reveal a lot about the people who made them.

“I knew beyond a shadow of a doubt that Bitcoin was not anonymous,” she said.

It turns out that you can find out a lot by looking at how Bitcoin transactions are related to each other. At the simplest level, if a string of Bitcoin characters starts many crypto transactions and another string, or wallet, receives them, which gives you a ratio to work with. So Meiklejohn decided to prove it in an unusual way: by acting.

Stefan Savage was her thesis advisor at UCSD. He still has a lot of the stuff she bought and he went through it. “So we have a Guy Fawkes mask – very popular at the moment – some earrings, organic Colombian coffee beans, I’m sure they’re still good after fifteen years,” he said.

This was part of the collection of things he and Meiklejohn bought with crypto to see the transactions go from buyer to seller.

“It was, I need to get a purchase from a wallet in this cluster that my algorithm has identified,” Savage said, explaining how they came to choose their purchases. “Let me go and see things that will probably bring me there.”

What Meiklejohn didn’t know at the time was a man’s name Michael Gronager followed her project and had read her research paper. He wrote an algorithm that would allow him to track transactions on a large scale.

In fact, he used that algorithm to figure out where a bunch of stolen Bitcoin had gone when a crypto exchange called Mt. Gox went bankrupt in 2014. He eventually turned all of this into the company Chainalysis.

He said his algorithm essentially automated and sweetened Meiklejohn’s tracking process. “I can see an automated pattern running all the time,” he said. Now he uses it to help financial institutions and governments track stolen money and identify bad players in the crypto world.

An earlier version of this story appeared on the Click Here podcast from Recorded Future News. Additional reporting by Sean Powers and Will Jarvis.