santhisenan/DeepDefense
DDoS attack detection using BLSTM based RNN
This project helps network administrators and security analysts identify Distributed Denial of Service (DDoS) attacks in network traffic. It takes raw network packet data, typically in a CSV format, and classifies it to flag malicious DDoS activity. The output helps security teams quickly detect and respond to ongoing attacks.
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Use this if you need to detect DDoS attacks on your network using a pre-trained deep learning model and have network flow data available in a structured format.
Not ideal if you are looking for a real-time, production-ready intrusion detection system or a solution that handles diverse attack types beyond DDoS.
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76
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26
Language
Jupyter Notebook
License
MIT
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Last pushed
May 03, 2020
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