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DataCrafters Dashboard

Overview

The DataCrafters Dashboard is a web application for analyzing and visualizing automotive cyber-attack datasets using advanced machine learning algorithms and interactive visualizations.

Features

Dynamic Visualizations

  • Interactive attack type distribution visualization with toggleable pie and bar chart views
  • Real-time animated trend analysis for attack progression patterns
  • Customizable correlation heatmaps for identifying attack relationships
  • Export capabilities for all visualization types

Advanced Analytics

  • Isolation Forest implementation for detecting anomalies in CAN bus data streams
  • Multi-model clustering approach combining DBSCAN and k-means for robust pattern identification
  • Configurable anomaly detection thresholds with preset recommendations
  • Historical pattern analysis with trend forecasting

Real-Time Integration

  • Mock API interface for development and testing
  • Websocket support for live data streaming
  • Configurable data refresh rates
  • Built-in data validation and sanitization

Alert System

  • Customizable email notifications for detected anomalies
  • Severity-based alert prioritization
  • Alert history tracking and analysis
  • Integration with popular notification platforms

Project Structure

project/
├── app/
│   ├── app.py                  # Flask application core
│   ├── config.py              # Configuration settings
│   └── templates/
│       ├── index.html         # Main dashboard interface
│       ├── analytics.html     # Analytics view
│       └── settings.html      # User settings panel
├── database/
│   ├── db_setup.py           # Database initialization
│   ├── db_queries.py         # Database utility functions
│   └── models.py             # Database models
├── visualizations/
│   ├── main_visualizer.py    # Streamlit visualization core
│   ├── anomaly_detection.py  # Anomaly detection algorithms
│   └── clustering_insights.py # Clustering analysis tools
├── static/
│   ├── css/
│   │   └── styles.css        # Application styling
│   └── js/
│       └── dashboard.js      # Frontend functionality
├── data/
│   ├── DoS_dataset.csv       # Denial of Service attack data
│   ├── Fuzzy_dataset.csv     # Fuzzing attack data
│   ├── gear_dataset.csv      # Gear manipulation data
│   └── RPM_dataset.csv       # RPM tampering data
├── tests/
│   ├── test_analytics.py     # Analytics unit tests
│   └── test_api.py          # API integration tests
├── requirements.txt          # Project dependencies
└── README.md                # This documentation

Installation

Prerequisites

  • Python 3.8 or higher
  • PostgreSQL 12+
  • Node.js 14+ (for frontend development)

Setup Instructions

  1. Clone the repository:

    git clone https://github.com/your-org/datacrafters-dashboard.git
cd datacrafters-dashboard

  2. Create and activate a virtual environment:

    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

  3. Install dependencies:

    pip install -r requirements.txt

  4. Configure the database:

    python database/db_setup.py

  5. Start the application:

    python app/app.py

Configuration

Create a .env file in the project root with the following variables:

DB_HOST=localhost
DB_PORT=5432
DB_NAME=datacrafters
DB_USER=your_username
DB_PASSWORD=your_password
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
SMTP_USER=your_email@gmail.com
SMTP_PASSWORD=your_app_password

Usage

  1. Access the dashboard at http://localhost:5000
  2. Upload your dataset through the data import interface
  3. Configure visualization parameters in the settings panel
  4. Set up email alerts for anomaly detection

Development

Running Tests

pytest tests/

Code Style

We follow PEP 8 guidelines. Run the linter:

flake8 .

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE file for more information.

Contact

Project Maintainer - @maintainer

Project Link: https://github.com/your-org/datacrafters-dashboard