kahramankostas/IoTGeM
IoT Attack Detection with machine learning
This project helps operations engineers or cybersecurity analysts detect attacks on Internet of Things (IoT) devices. It takes raw network traffic data, typically captured in PCAP files, and processes it to identify unusual behavior indicative of cyberattacks. The output is a machine learning model capable of early and accurate attack detection across various IoT environments.
No commits in the last 6 months.
Use this if you need to build a robust, generalizable system for identifying cyber threats targeting a diverse fleet of IoT devices using their network behavior.
Not ideal if you are looking for a pre-built, ready-to-deploy commercial intrusion detection system rather than a research-oriented machine learning implementation.
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30
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7
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 12, 2025
Commits (30d)
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