tamimmirza/Intrusion-Detection-System-using-Deep-Learning
VGG-19 deep learning model trained using ISCX 2012 IDS Dataset
This project helps network security analysts detect cyber intrusions by analyzing network traffic data. It takes raw network packet captures (PCAP files) and processes them through a deep learning model to identify potential attack patterns, flagging suspicious activities for further investigation. It is intended for cybersecurity professionals or network operations centers responsible for monitoring network health and security.
145 stars. No commits in the last 6 months.
Use this if you need an automated way to analyze network traffic for intrusion detection using a deep learning approach.
Not ideal if you lack the powerful computing hardware (GPU, CUDA) required for deep learning model training, as performance will be severely impacted.
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Jan 05, 2019
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