Mamcose/NSL-KDD-Network-Intrusion-Detection

Machine Learning Algorithms on NSL-KDD dataset

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This project helps network security professionals identify cyberattacks by analyzing network traffic data. It takes raw network connection logs as input and outputs classifications of whether a connection is normal or an intrusion, helping to flag suspicious activity. This is intended for network administrators, security analysts, or anyone responsible for maintaining network integrity.

No commits in the last 6 months.

Use this if you need to automatically detect common network intrusions by applying machine learning models to your network flow data.

Not ideal if you require real-time, high-performance intrusion detection for large-scale, live network environments without a pre-existing dataset for training.

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

Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 9 / 25

Maturity 16 / 25

Community 21 / 25

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Jupyter Notebook

License

GPL-3.0

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

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