siri-vyshnavi/PasswordStrengthDetection

🔐 Quantum Password Strength Classifier

A Variational Quantum Classifier (VQC) for password strength classification using PennyLane.

Model Architecture

• —Qubits: 8 (one per feature)
• —Encoding: Multi-Resolution Dual RY Gates
• —Layer 1: RY(x) - Full resolution
• —Layer 2: RY(0.5x) - Half resolution
• —Variational Layers: 3 layers with RY + RZ rotations
• —Entanglement: Ring topology (circular CNOT chain)
• —Output: 3-class classification (Weak, Medium, Strong)

Features Extracted

1. 1.Normalized length (max 20 chars)
2. 2.Has lowercase letters
3. 3.Has uppercase letters
4. 4.Has digits
5. 5.Has special characters
6. 6.Character diversity ratio
7. 7.Digit ratio
8. 8.Special character ratio

Performance

• —Test Accuracy: ~90%
• —Dataset: 3,000 balanced passwords (1,000 per class)

Technologies

• —PennyLane - Quantum Machine Learning
• —Gradio - Web Interface
• —scikit-learn - Preprocessing

Authors

Built as an academic project demonstrating Quantum Machine Learning for cybersecurity applications.

License

MIT License