In the evolving landscape of automotive technology, securing in-vehicle networks is crucial. The proposition involves a Machine Learning-based Intrusion Detection System (IDS) with a multi-tier hybrid architecture that integrates both signature-based detection (Supervised learning) and anomaly-based detection (Unsupervised learning). This approach combines the accuracy of signature-based detection for known threats with the adaptability of anomaly-based detection methods for new threats, offering a robust and comprehensive security solution for vehicular networks.

• Projects entry point is app.py in the root directory
• Run python app.py in root folder to execute the program

To learn more checkout the Documentation here

@Vangerwua Johnpaul (2024).