janerjzou/AD_FL_DL
Apply Federated Learning and Deep Learning (Deep Auto-encoder) to detect abnormal data for IoT devices.
This project helps operations engineers or cybersecurity analysts detect unusual behavior in IoT devices. It takes data streams from various IoT devices as input and identifies whether the device's activity is normal or anomalous. This is useful for monitoring the health and security of connected devices without centralizing all sensitive data.
No commits in the last 6 months.
Use this if you need to detect abnormal data or potential cyber threats across multiple IoT devices while prioritizing data privacy and minimizing central data sharing.
Not ideal if you need to detect anomalies in non-IoT data, or if you can consolidate all device data into a single location for analysis.
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Last pushed
Aug 16, 2022
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