aaaastark/Intrusion-Detection-System
Attack Detection, Parameter Optimization and Performance Analysis in Enterprise Networks (ML Networks) for Intrusion Detection System IDS.
This project helps cybersecurity professionals analyze network traffic data to detect and classify cyberattacks. By inputting network logs, it identifies whether traffic is benign or malicious, and further categorizes specific attack types like DoS/DDoS or PortScan. Network security analysts and incident responders would use this to enhance their intrusion detection systems.
No commits in the last 6 months.
Use this if you are a cybersecurity professional evaluating or optimizing intrusion detection systems using machine learning and real-world network traffic datasets.
Not ideal if you are looking for an off-the-shelf, deployable intrusion detection system for immediate network protection.
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License
MIT
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Last pushed
Oct 31, 2023
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