Securing Transit Data: Integrity Protection for Online Transportation System

The increasing reliance on cloud-based technologies in transportation systems has raised significant cybersecurity concerns. As digital infrastructure expands, protecting transit data from cyber threats becomes critical. This project presents an AI-driven framework that uses honeypots to gather real attack data and machine learning models to detect and classify threats in instantly and continuously. The system enables scalable, cloud-based monitoring and automated alerts for rapid response. Testing shows over 92% accuracy in threat detection, validating the framework's effectiveness in enhancing transportation data security.