DataHacks 2021: Bitcoin Ransomware Classification

Project Overview

The UCSD DataHacks 2021 featured an Intermediate level project on Bitcoin ransomware. The goal of the project was to “Define a machine learning model most appropriate for classifying heist incidents into ransomware families. Then, define a model to predict if a future transaction is a ransom or not, and if it is, the ransomware family it belongs to.”

The project was quite a challenge because everyone on my team was fairly new to machine learning, but we adapted quickly to the prompt’s demands and submitted a complete report to the panel of professionals within 36 hours. Through this competition, I learned how to identify trends in a dataset using various plots and classify Bitcoin transactions using basic algorithms from the Sklearn library. Although the whole competition was remote, I had a blast working with this team of UCSD students formed on the spot, and look forward to more competitions in the future!

Results

Bitcoin Ransomware Classification Project Report