Ransomware Detection on the Bitcoin Blockchain

using Random Forests and Self Organizing Maps

Final submission for CYO project at HarvardX PH125.9x Capstone Course

Machine learning project on BitcoinHeist data set.

https://archive.ics.uci.edu/ml/datasets/BitcoinHeistRansomwareAddressDataset

Most of these files are exploratory scripts that helped to develop the final script.

The main three files that can be considered the final project are:

• Detecting_Bitcoin_Ransomware.pdf (Final report) https://git.disroot.org/shelldweller/ransomware/raw/branch/master/Detecting_Bitcoin_Ransomware.pdf

• Detecting_Bitcoin_Ransomware.Rmd (R markdown that generates the report) https://git.disroot.org/shelldweller/ransomware/raw/branch/master/Detecting_Bitcoin_Ransomware.Rmd

• Detecting_Bitcoin_Ransomware.R (R script that contains the essential code for the modeling process) https://git.disroot.org/shelldweller/ransomware/raw/branch/master/Detecting_Bitcoin_Ransomware.R

Everything else can be safely ignored, and is just here so that I can trace my own steps if needed.

Detecting Bitcoin Ransomware by KR Tejeda is licensed under a Creative Commons Attribution 4.0 International License.
Based on a work at https://arxiv.org/abs/1906.07852.