CynthiaKoopman/Network-Intrusion-Detection

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

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This project helps network security analysts evaluate the effectiveness of different machine learning models in identifying network intrusions. By inputting network traffic data, it generates analyses to show how well methods like Decision Trees and Random Forests can detect suspicious activity. It's designed for cybersecurity professionals responsible for safeguarding network infrastructure.

271 stars. No commits in the last 6 months.

Use this if you need to compare different machine learning techniques for detecting network intrusions and want to understand their performance.

Not ideal if you are looking for a plug-and-play intrusion detection system rather than a tool for analyzing and comparing detection models.

network-security intrusion-detection cybersecurity-analysis network-monitoring

No License Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 10 / 25

Maturity 8 / 25

Community 24 / 25

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Network-Intrusion-Detection and Network-Intrusion-Detection-Using-Machine-Learning-Techniques Network-Intrusion-Detection and NSL-KDD-Network-Intrusion-Detection

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