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.pyin the root directory - Run
python app.pyin root folder to execute the program
To learn more checkout the Documentation here
@Vangerwua Johnpaul (2024).