ReubenJoe/DDoS-Detection
Detailed Comparative analysis of DDoS detection using Machine Learning Models
This project helps network security teams and operations engineers identify Distributed Denial of Service (DDoS) attacks. It takes network traffic data as input and uses various machine learning models to classify whether the traffic is normal or part of a DDoS attack. The output helps security professionals quickly detect and respond to these critical threats.
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Use this if you need to detect DDoS flooding attacks on your network using machine learning and want to compare different model performances.
Not ideal if you are looking for a plug-and-play solution for attack mitigation rather than a comparative analysis of detection algorithms.
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Jun 14, 2022
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