Intrusion Detection System with Machine Learning

It is important to launch this project with the python virtual environment (.venv). If your python interpreter is not in the project order, please replace the variable python_executable in the file main.py with the path to your python interpreter.

Packages needed to be installed:

• scapy
• duckdb
• sklearn
• seaborn
• matplotlib
• numpy
• scikit-learn
• pandas
• tkinter
• os
• sys

Modules Roadmap:

• Module 1: Package capture
• Module 2: Rule-based detection
  • 1. Checksom Verification
  • 2. Payload Pattern Matching
  • 3. Rate-Based Anomaly Detection
  • 4. Malformed Packet Detection
  • 5. ICMP Flood Detection
  • 6. DNS Spoofing Detection
  • 7. ARP Spoofing Detection
  • 8. Protocol-Specific Anomalies
    • 8.1 Fragment checks
    • 8.2 Valid Handshake Check
  • 9. Content-Learning Mismatch
  • Additional checks:
    • IP Spoofing Detection
    • SYN FIN Combination Detection
    • null Packet Detection
    • Malicious Ports Detection
    • More DNS Spoofing Detection
    • Destination Checks
    • TCP reset Detection
• Module 3: Anomaly-based detection
  • Logistic Regression
  • Decision Tree Classifier
  • KNN
  • Random Forest