Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
This project helps cybersecurity professionals and network engineers identify cyber-attacks in connected vehicle networks. It takes network traffic data as input and outputs classifications of known or unknown intrusion attempts. The end-user persona is likely a security analyst or an operations engineer responsible for securing Internet of Vehicles (IoV) infrastructure.
573 stars. No commits in the last 6 months.
Use this if you need to develop or implement a machine learning-based intrusion detection system specifically for vehicular networks, including both in-vehicle and external communications.
Not ideal if your primary focus is on general enterprise network security or if you require an IDS that does not use machine learning techniques.
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573
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155
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Jupyter Notebook
License
MIT
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Last pushed
Aug 06, 2025
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