Giter Club home page Giter Club logo

ethereum-bot-detection's Introduction

Ethereum

Bot Detection This code was used to generate results presented in the paper "Detecting Financial Bots on the Ethereum Blockchain".

Bot Image width=

Note that the methods used in this paper are compute intensive for a single PC and require 64GB of RAM. On an AMD Ryzen 5 2600 Six-Core Processor (3.4 GHz) with 64GB of RAM, the code takes about 24 hours to run and in addition to the results produced for the paper, several other tables and figures are generated.

How to install

This repository has only been tested on Windows 10 but may also work on Linux distributions.

To install the required python packages use the following commands

python -m venv .venv
.venv/Scripts/activate source 
pip install requirements.txt

or on Linux (untested)

python -m venv .venv
source .venv/bin/activate
pip install requirements.txt

Minimal Example

Setup

To use this repository block, transaction, and log data (enriched as provided by graphsense-lib) are required

To use it, point PREFIX_DB in configs/test.toml to the folder containing the raw data as demonstrated in a test sample provided in test_data/test_run.

Furthermore, a trace_creations.csv file is required that contains all addresses that should be marked as a smart contract A minimal example is also provided in test_data/codes. Note that the content of the output column is not of central importance. As soon as an address appears in the to_address column, it will be marked as a smart contract.

The data is provided to the program in a compressed format as demonstrated in the minimal example.

Run

To run the code use the following command

python pipeline.py

Tables and figures will be saved in the output folder.

Acknowledgements

We use MEV-inspect https://github.com/flashbots/mev-inspect-py/tree/main/mev_inspect with slightly adapted code to work with data provided by graphsense-lib https://github.com/graphsense/graphsense-lib.

ethereum-bot-detection's People

Contributors

tommel71 avatar

Stargazers

 avatar  avatar

Watchers

 avatar

Forkers

machercs

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.