WalkingDevFlag/CICIDS-2017
Jupyter notebooks for analyzing the CICIDS 2017 dataset, to download data, EDA, and training various classification models and deep learning architectures.
This project offers a collection of Jupyter notebooks for analyzing the CICIDS 2017 dataset, which contains network traffic data with various types of cyberattacks. It provides tools to explore the dataset, prepare it for analysis, and train machine learning models to identify intrusions. A cybersecurity analyst or researcher would use this to understand network attack patterns and build effective intrusion detection systems.
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Use this if you are a cybersecurity professional or researcher looking to study network intrusion detection, using the CICIDS 2017 dataset to develop and benchmark threat detection models.
Not ideal if you need to analyze a different network traffic dataset or require a pre-built, production-ready intrusion detection system rather than a research framework.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Nov 24, 2024
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