Autoforensics - Smart Vehicular Forensics Tool

Advanced forensic analysis tool for detecting security threats in smart vehicular networks.

Features

• Sybil Attack Detection: Identify malicious nodes creating multiple fake identities
• Position Falsification Detection: Detect vehicles broadcasting false GPS coordinates
• Automated Analysis: Python-based backend for comprehensive forensic investigation
• PDF Report Generation: Professional forensic reports with detailed findings
• Modern Web Interface: React-based frontend with intuitive user experience

Project Structure

autoforensics/
├── backend/
│   ├── app.py                          # Flask application
│   ├── config.py                       # Configuration
│   ├── requirements.txt                # Python dependencies
│   ├── forensics/
│   │   ├── __init__.py
│   │   ├── sybil_attack.py            # Sybil detection logic
│   │   └── position_falsification.py  # Position detection logic
│   ├── utils/
│   │   ├── __init__.py
│   │   ├── file_handler.py            # File operations
│   │   └── pdf_generator.py           # PDF generation
│   └── uploads/                        # Temporary file storage
├── frontend/
│   ├── public/
│   │   └── index.html
│   ├── src/
│   │   ├── App.js                     # Main component
│   │   ├── index.js                   # Entry point
│   │   ├── index.css                  # Global styles
│   │   └── services/
│   │       └── api.js                 # API service
│   └── package.json
└── README.md

Installation

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Create a virtual environment:

python -m venv venv

3. Activate the virtual environment:

   • Windows: venv\Scripts\activate
   • macOS/Linux: source venv/bin/activate

4. Install dependencies:

pip install -r requirements.txt

5. Create necessary directories:

mkdir uploads reports

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

Running the Application

Start Backend Server

cd backend
python app.py

The backend will run on http://localhost:5000

Start Frontend Development Server

cd frontend
npm start

The frontend will run on http://localhost:3000

Usage

1. Upload File: Select a forensic data file (CSV, JSON, TXT, LOG)
2. Choose Analysis: Select either Sybil Attack or Position Falsification analysis
3. Review Results: Examine detailed findings and threat indicators
4. Download Report: Export comprehensive PDF forensic report

Implementing Your Investigation Logic

Sybil Attack Detection

Edit backend/forensics/sybil_attack.py:

def analyze(self, filepath: str) -> Dict[str, Any]:
    # Your investigation logic here
    # 1. Extract vehicle identities
    # 2. Analyze identity patterns
    # 3. Check for duplicate behaviors
    # 4. Calculate threat level
    pass

Position Falsification Detection

Edit backend/forensics/position_falsification.py:

def analyze(self, filepath: str) -> Dict[str, Any]:
    # Your investigation logic here
    # 1. Extract GPS data
    # 2. Validate coordinates
    # 3. Analyze movement patterns
    # 4. Detect impossible movements
    pass

API Endpoints

• GET /api/health - Health check
• POST /api/upload - Upload file for analysis
• POST /api/analyze/sybil - Analyze for Sybil attack
• POST /api/analyze/position - Analyze for position falsification
• POST /api/download/pdf/<type> - Download PDF report
• DELETE /api/cleanup/<filename> - Clean up uploaded file

Configuration

Edit backend/config.py to modify:

• Upload folder location
• Maximum file size
• Allowed file extensions
• Session timeout
• CORS origins

File Format Requirements

CSV Format

vehicle_id,timestamp,latitude,longitude,speed,...
VEH001,2024-01-01T10:00:00,23.0225,72.5714,45,...

JSON Format

{
  "vehicles": [
    {
      "id": "VEH001",
      "timestamp": "2024-01-01T10:00:00",
      "position": {"lat": 23.0225, "lon": 72.5714},
      "speed": 45
    }
  ]
}

Security Considerations

• File uploads are sanitized and validated
• Files are stored with unique timestamps
• Automatic cleanup of old files
• CORS configuration for allowed origins
• Input validation on all endpoints

Development

Adding New Analysis Types

1. Create new detector class in backend/forensics/
2. Add API endpoint in backend/app.py
3. Create report page component in frontend
4. Update API service in frontend/src/services/api.js

Customizing PDF Reports

Edit backend/utils/pdf_generator.py to modify:

• Report layout and styling
• Sections and content
• Tables and visualizations
• Header and footer

Troubleshooting

Backend Issues

• Port already in use: Change port in app.py
• Module not found: Ensure virtual environment is activated
• File upload fails: Check uploads/ directory permissions

Frontend Issues

• API connection fails: Verify backend is running on port 5000
• Module not found: Run npm install
• Build fails: Clear node_modules and reinstall

License

[Your License Here]

Contact

[Your Contact Information]

Acknowledgments

Developed for vehicular network security research and forensic analysis.