/Intrusion-Detection-Ensemble-Learning-and-Packet-Sniffer

•Intrusion detection system that is able to classify a malicious packet into one of intrusion attack classes based upon its attributes. •Aiming to use a number of classifying algorithms like random forests, decision tree will be used and bagged together. •Used web sniffer to analyze real time Internet traffic as an extension.

Primary LanguageJupyter Notebook

Network Intrusion Detection System

Intrusion detection system is able to classify a malicious packet into intrusion attack classes based upon the ML Model Prediction. Network sniffer is used to analyze real time network traffic at an interface and parse into NSL-KDD99 attributes. network intrusion detector model predict the legitimacy of the packets with an accuracy of ~94%.


Intrusion detection system is able to classify a malicious packet into intrusion attack classes based upon the ML Model Prediction.
Network sniffer is used to analyze real time network traffic at an interface and parse into NSL-KDD99 attributes.
Network intrusion detector model predict the legitimacy of the packets with an accuracy of ~94%.

How To Run the Code

  • Ensure necessary packages stated requirement.txt are installed.
  • Create Model by running model_generation .
  • Run start.sh file in Linux terminal.