abhinav-bhardwaj/IoT-Network-Intrusion-Detection-System-UNSW-NB15
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
This project helps operations engineers or cybersecurity analysts monitor IoT network traffic to detect and classify cyberattacks. It takes raw network data from an IoT environment, processes it, and then identifies if traffic is normal or abnormal. If abnormal, it further categorizes the specific type of attack (e.g., Denial of Service, Exploits).
197 stars. No commits in the last 6 months.
Use this if you need to analyze IoT network traffic data to automatically identify and classify various types of cyberattacks.
Not ideal if you require a real-time, deployed solution for live network monitoring, as this project focuses on offline analysis of datasets.
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License
MIT
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Last pushed
Sep 08, 2021
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