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GauravPatel44/Ai_Based_Network_Intrusion_detection

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๐Ÿ›ก๏ธ AI-Based Network Intrusion Detection System (Student Project)

This project demonstrates how to use Machine Learning (Random Forest) and Generative AI (Grok) to detect and explain network attacks (specifically DDoS).

๐Ÿš€ How to Use

  1. 1.Enter API Key: Paste your Grok API key in the sidebar (optional, for AI explanations).
  2. 2.Train Model: Click the "Train AI Model" button. The system loads the Friday-WorkingHours... dataset automatically.
  3. 3.Simulate: Click "Simulate Random Packet" to pick a real network packet from the test set.
  4. 4.Analyze: See if the model flags it as BENIGN or DDoS, and ask Grok to explain why.

๐Ÿ“‚ Files

  • โ€”app.py: The main Python application code.
  • โ€”requirements.txt: List of libraries used.
  • โ€”Friday-WorkingHours-Afternoon-DDos.pcap_ISCX.csv: The dataset (CIC-IDS2017 subset).

๐ŸŽ“ About

Created for a university cybersecurity project to demonstrate the integration of traditional ML and LLMs in security operations.