This project is a real-time intrusion detection system built using machine learning. We created a custom dataset of both attack and benign traffic using tools like GoldenEye and Apache Benchmark, and extracted flow-level features using NTLFlowLyzer. Our trained model classifies live network traffic as either attack or benign with high accuracy. This solution was developed to overcome limitations in existing IDS tools and to explore scalable, AI-powered security applications for modern networks.
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