Dark Web Bitcoin Crawling and Visualization

A project designed to crawl the dark web to extract Bitcoin wallet addresses and visualize their transaction graphs for analysis.

Features

1. Dark Web Crawling: Extract Bitcoin addresses from .onion sites using the Tor network.
2. Data Storage: Store crawled data, metadata, and transaction details in a MongoDB database.
3. Graph Visualization: Visualize Bitcoin transactions and wallet connections using an interactive graph.

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Project Setup

Prerequisites

• Tor Browser: Required for crawling .onion websites. Install it from Tor Project.
• Python: Version 3.7 or higher.
• MongoDB: Install and set up MongoDB for storing crawled data.
• GeckoDriver: Required for controlling the Firefox browser used by tbselenium. Download it from Mozilla GeckoDriver Releases.
  • Important: Ensure that the GeckoDriver is added to your system's PATH variable. This step is compulsory for the application to work correctly.

Installation

1. Clone this repository:

   git clone <repository-url>
   cd DarkWebCryptoHunter
   

2. Install Python dependencies:

   pip install -r requirements.txt
   

3. Configure the project:

   • Update the config.py file with the following:
     • TOR_PATH: Path to your Tor browser.
     • DB_NAME: Name of the MongoDB database.
     • URL: Seed .onion URL for the crawler.

4. Start MongoDB:

   mongod --dbpath <your-db-path>
   
   

Usage

Start Crawling

Run the main.py script to initiate the crawling process:

python backend/main.py

Visualize Data

Open the frontend:

cd frontend
open index.html

The Graph Displays:

• Nodes: Bitcoin wallet addresses.
• Edges: Transactions between addresses.

Directory Structure

DarkWebCryptoHunter/
│
├── frontend/                         # Frontend for visualization
│   ├── index.html                    # Main webpage
│   ├── css/
│   │   └── style.css                 # Styles for the website
│   └── js/
│       └── script.js                 # Logic for graph visualization
│
├── backend/                          # Backend for crawling and processing data
│   ├── crawler.py                    # Dark web crawler
│   ├── database.py                   # Handles database operations
│   ├── bitcoin_address_extractor.py  # Extracts Bitcoin addresses from raw data
│   ├── config.py                     # Configuration constants
|   ├── analysis.py                   # Analyze the extracted addresses to generate graphs
│   └── main.py                       # Entry point for backend logic
│
├── requirements.txt                  # Python dependencies
└── README.md                         # Project documentation

Further Development

While the current implementation provides static data visualization, the following enhancements can be added:

1. Real-Time Crawling: Enable live crawling of the dark web for updated Bitcoin transaction data.
2. Advanced Analytics: Add statistical analysis features to identify suspicious patterns automatically.
3. Depth Customization: Allow users to customize the depth of transaction analysis in the graph.