Ethereum-Fraud-Detection

Installing required modules and packages.

Backend is written in python.
For backend folder files, paste the following code in the terminal to automatically install all the required packages.
pip install -r requirements.txt

For frontend we are using React with vite, so just type in the following code in terminal after entering the Frontend folder.
npm i

Run the server.py file to start a flask server.

This file is responsible for the communication between frontend and backend.

Start the frontend server with following command.

npm run dev

Ethereum_Fraud_Detection.joblib is the saved Machine Learning Model in serialized form which is loaded to predict the possible outcome in server.py file.

X_Address.joblib is the training X values which are saved and loaded in server.py file for getting the features because currently we dont have a proper backend.

Only the addresses listed in X_Address.joblib will be predicted for now.