A method for visual analysis of token transaction data on the blockchain to quickly identify suspicious transactions.

Please follow the steps below to install and configure this project :

STEP 1:

git clone https://github.com/peculab/TrackingCarbon.git

STEP 2: Setup virtual environment and install dependencies using pip install -r requirements.txt

STEP 3: Replace the credentials in the .env file with your own API_KEYS

🎞️Video demonstration: Visualization Techniques for Tracking Carbon Credit Trading Pathways

Here are instructions on how to use this project.

Obtaining Multi-layer Historical Transaction Data for a Wallet:

1. Copy the wallet address(es) you want to track and paste them into the INITIAL_ADDRESSES in the main function on line 84 of the file data_collection.py.

2. Modify the MAX_DEPTH parameter in the .env file according to the maximum number of layers you want to track.

3. Adjust the TX_COUNT_THRESHOLD in .env to set the number of transactions per layer you want to track ( Note: If no limit is set, the process may take several hours).

4. Run the script:

py data_collection.py

5. Obtain the CSV file.

Obtaining Single-layer Historical Transaction Data for a Wallet:

1. Directly download the transaction data from Etherscan.

1. Replace 'path/to/your/csvfile.csv' in the file_path variable with the path to your CSV file containing the transaction data. This can be found in the main function on line 7 of the file graph.py.
2. Run the application:

python graph.py

3. Open a web browser and navigate to the address in the command line (usually http://127.0.0.1:8050/) to view the dashboard.

What Addresses are Potential Fraud Accounts?