This project explores integrating the Advanced Encryption Standard (AES) algorithm into cybersecurity solutions for IoT systems, such as autonomous vehicles (AVs) and cloud data storage. Combining AES encryption with AI techniques (Machine Learning) enhances data transmission security.
- Features
- Technologies Used
- Key Components
- Performance Evaluation
- Business Applications
- Installation
- Usage
- Contributing
- License
- Contact
- 512-bit AES encryption for secure data transmission
- Dual encryption for AV communication security
- AI/ML-based malware detection in cloud data
- Performance evaluation of encryption/decryption methods
- Encryption: AES (512-bit)
- AI/ML: Artificial Neural Network (ANN), Particle Swarm Optimization (PSO)
- Languages: Python
- Cloud Services: Gcloud
- AES Algorithm: Uses 512-bit AES encryption to enhance security.
- Cybersecurity in AVs: Protects AV sensor data with dual encryption.
- AI/ML in Cybersecurity: Custom ANN + PSO algorithm for malware detection in cloud storage.
Analyzes encryption/decryption methods, showing AES combined with AI improves security against common attacks (MiM, DoS) and optimizes encryption/decryption times.
Useful for autonomous vehicle networks and cloud infrastructure, where secure data transmission is critical.
pip install -r requirements.txt
Usage
bash
Copy code
python main.py
Contributing
Fork this repository, make your changes, and submit a pull request. For issues, open a new ticket in the issues section.